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Prompt-to-video
Year
2024
Event
GAI Learning Lab
Focus
AI, storytelling, video production, creativity, generative media
Overview
This talk explores how text-to-video is changing the way creators turn ideas into visual stories. I introduced text-to-video as the next step after text-to-text, text-to-image, and text-to-music: a workflow where written prompts or still images can become short video clips. The talk focused on how these tools can support marketing content, educational content, visual storytelling, and rapid concept exploration.
The core idea of the talk is that text-to-video is not just a production shortcut. It is a new creative interface. I showed how creators can use tools like Runway ML to add motion, atmosphere, camera movement, and cinematic effects to still images. The session included a live demo using a still image of the Charles River and a prompt that transformed it into a cinematic scene with a sea creature emerging from the water.
I also compared traditional production stages — pre-production, production, and post-production — with an AI-assisted workflow using tools like ChatGPT or Claude for scripting, Midjourney for visuals, Runway and Luma AI for video generation, ElevenLabs for voiceover, and AI music tools for sound.
Key Ideas
- Text-to-video makes it easier to turn concepts and imagination into visual stories.
- AI video tools are useful for early ideation, concept development, storytelling, and rapid prototyping.
- The current workflow still requires creative direction, prompt iteration, editing judgment, and tool selection.
- AI can support multiple stages of production, from scripting and asset generation to video generation and post-production.
- Character consistency, lip sync, and cinematic motion are improving quickly, but still require workarounds.
- Text-to-video does not fully replace traditional production, but it can complement and accelerate parts of the workflow.
- Copyright, licensing, training-data transparency, and commercial usage rights are important when using AI-generated media professionally.
© 2026 Sarat Kollimarla · Updated June 2026
.
Back to home
Prompt-to-video
Year
2024
Event
GAI Learning Lab
Focus
AI, storytelling, video production, creativity, generative media
Overview
This talk explores how text-to-video is changing the way creators turn ideas into visual stories. I introduced text-to-video as the next step after text-to-text, text-to-image, and text-to-music: a workflow where written prompts or still images can become short video clips. The talk focused on how these tools can support marketing content, educational content, visual storytelling, and rapid concept exploration.
The core idea of the talk is that text-to-video is not just a production shortcut. It is a new creative interface. I showed how creators can use tools like Runway ML to add motion, atmosphere, camera movement, and cinematic effects to still images. The session included a live demo using a still image of the Charles River and a prompt that transformed it into a cinematic scene with a sea creature emerging from the water.
I also compared traditional production stages — pre-production, production, and post-production — with an AI-assisted workflow using tools like ChatGPT or Claude for scripting, Midjourney for visuals, Runway and Luma AI for video generation, ElevenLabs for voiceover, and AI music tools for sound.
Key Ideas
- Text-to-video makes it easier to turn concepts and imagination into visual stories.
- AI video tools are useful for early ideation, concept development, storytelling, and rapid prototyping.
- The current workflow still requires creative direction, prompt iteration, editing judgment, and tool selection.
- AI can support multiple stages of production, from scripting and asset generation to video generation and post-production.
- Character consistency, lip sync, and cinematic motion are improving quickly, but still require workarounds.
- Text-to-video does not fully replace traditional production, but it can complement and accelerate parts of the workflow.
- Copyright, licensing, training-data transparency, and commercial usage rights are important when using AI-generated media professionally.
© 2026 Sarat Kollimarla · Updated June 2026
.
Back to home
Prompt-to-video
Year
2024
Event
GAI Learning Lab
Focus
AI, storytelling, video production, creativity, generative media
Overview
This talk explores how text-to-video is changing the way creators turn ideas into visual stories. I introduced text-to-video as the next step after text-to-text, text-to-image, and text-to-music: a workflow where written prompts or still images can become short video clips. The talk focused on how these tools can support marketing content, educational content, visual storytelling, and rapid concept exploration.
The core idea of the talk is that text-to-video is not just a production shortcut. It is a new creative interface. I showed how creators can use tools like Runway ML to add motion, atmosphere, camera movement, and cinematic effects to still images. The session included a live demo using a still image of the Charles River and a prompt that transformed it into a cinematic scene with a sea creature emerging from the water.
I also compared traditional production stages — pre-production, production, and post-production — with an AI-assisted workflow using tools like ChatGPT or Claude for scripting, Midjourney for visuals, Runway and Luma AI for video generation, ElevenLabs for voiceover, and AI music tools for sound.
Key Ideas
- Text-to-video makes it easier to turn concepts and imagination into visual stories.
- AI video tools are useful for early ideation, concept development, storytelling, and rapid prototyping.
- The current workflow still requires creative direction, prompt iteration, editing judgment, and tool selection.
- AI can support multiple stages of production, from scripting and asset generation to video generation and post-production.
- Character consistency, lip sync, and cinematic motion are improving quickly, but still require workarounds.
- Text-to-video does not fully replace traditional production, but it can complement and accelerate parts of the workflow.
- Copyright, licensing, training-data transparency, and commercial usage rights are important when using AI-generated media professionally.
© 2026 Sarat Kollimarla · Updated June 2026
.