AI Text-to-Video done locally (edge) on a common 4070 RTX GPU Gaming PC.
This video showcases the creation of a Python application using the Paird.ai node tree process, which completely eliminates the need for traditional prompt generation methods. The nodes generate highly optimized prompts, resulting in precise and efficient code output. Operating at speeds unmatched by any other AI tool on the market, I was able to build a graphical user interface (GUI) and an automated workflow for an AI text-to-video storyboard pipeline, that I call 'Autoplay', in under 45 minutes. The application runs locally on standard gaming PC hardware.
What truly sets this tool apart is its ability to generate multiple storyboard columns, each with its own prompt, and support unlimited video iterations. With just an RTX 4070 GPU, I'm able to produce a 6-second video every 6-10 minutes, allowing for the creation of a vast collection of videos ready for editing and refinement after an overnight batch render—an absolutely incredible capability.
My Python app automatically downloads all the necessary AI models, so there's no need for crazy complicated tools like ComfyUI. The end result is a fully modular and scalable Python program that doesn't require deep knowledge of the underlying code. Most of the process is as simple as copying and pasting code directly from Paird.ai. By releasing this project as open-source, I hope to encourage further development and collaboration.
Oh yeah, the music is AI generated too.
Fork the nodes so you can create your own app:
https://paird.ai/forumDetail/ai-text-to-video-done-locally-edge-on-a-common-4070-rtx-gpu-gaming-pc
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Paird.ai - Code an API endpoint in 8 minutes
Seamlessly toggle between multiple AI models, such as Groq, OpenAI-40-mini, and Claude Sonnet 3.5, to refine your code in a non-linear way. Invite your friends to code with you. Iterate, refine, share, and collaborate with ease. Paird makes it effortless. Start by learning the basics and see how you can create a robust API endpoint in just minutes using the simplest prompts. Speed of iteration is the key to elegant software.
AI Text-to-Video done locally (edge) on a common 4070 RTX GPU Gaming PC.
This video showcases the creation of a Python application using the Paird.ai node tree process, which completely eliminates the need for traditional prompt generation methods. The nodes generate highly optimized prompts, resulting in precise and efficient code output. Operating at speeds unmatched by any other AI tool on the market, I was able to build a graphical user interface (GUI) and an automated workflow for an AI text-to-video storyboard pipeline, that I call 'Autoplay', in under 45 minutes. The application runs locally on standard gaming PC hardware. What truly sets this tool apart is its ability to generate multiple storyboard columns, each with its own prompt, and support unlimited video iterations. With just an RTX 4070 GPU, I'm able to produce a 6-second video every 6-10 minutes, allowing for the creation of a vast collection of videos ready for editing and refinement after an overnight batch render—an absolutely incredible capability. My Python app automatically downloads all the necessary AI models, so there's no need for crazy complicated tools like ComfyUI. The end result is a fully modular and scalable Python program that doesn't require deep knowledge of the underlying code. Most of the process is as simple as copying and pasting code directly from Paird.ai. By releasing this project as open-source, I hope to encourage further development and collaboration. Oh yeah, the music is AI generated too. Fork the nodes so you can create your own app: https://paird.ai/forumDetail/ai-text-to-video-done-locally-edge-on-a-common-4070-rtx-gpu-gaming-pc