The First High Res FREE & Open Source AI Video Generator!
TLDRThe video introduces 'Potate One', the first high-resolution, free, and open-source AI video generator. It positions itself as a competitor to Runway ML's Gen 2, offering higher frame rates and resolutions. The generator is based on Model Scope AI and allows users to create videos with better coherency and quality. The video showcases various demo outputs, highlights the ease of use through Google Collab, and teases the upcoming 'Potate 2' with promises of further improvements. The open-source nature is emphasized, inviting community contributions to enhance the model.
Takeaways
- 😀 AI text generation and text-to-image generation are currently the most popular forms of AI, with the latter being a close second.
- 🔍 The next step in AI image generation is AI video generation, which has seen significant developments but limited public access.
- 🚀 Google's Imogen video is an example of AI video generation, but it's not publicly available; Runway ML's Gen 2 is currently the most accessible.
- 🌟 The open-source 'Potato One' is a new competitor to Gen 2, offering higher frame rates and resolutions for text-to-video generation.
- 📹 Potato One is based on the Model Scope AI video generator, which was an early attempt at AI video generation with limited quality.
- 🎉 Potato One can generate videos at 1024 by 576 resolution, marking a step into HD territory for open-source text-to-video models.
- 🛠️ The open-source nature of Potato One allows for community modification and improvement, enhancing its capabilities over time.
- 🔗 Potato One can be run on Google Colab with 15 GB of RAM, making it accessible for free to those without high-end hardware.
- 👨💻 The model's coherency and resolution are impressive for an open-source project, with potential for further improvement.
- 🔄 Potato One supports negative prompts and customization options, including steps per frame and total frames per second.
- 🔄 The generation process is time-consuming, especially on free platforms like Google Colab, but could be faster with better resources.
Q & A
What is the significance of the AI video generator discussed in the transcript?
-The AI video generator, known as 'potate one', is significant because it is the first high-resolution, free, and open-source AI video generator. It allows for the creation of higher frame rate and higher resolution videos compared to previous models, and being open-source, it enables users to modify and improve upon it.
What are the two main forms of AI mentioned in the transcript?
-The two main forms of AI mentioned are AI text generation, such as chatbots, and text to image generation and manipulation.
What is the resolution of the videos generated by 'potate one'?
-The 'potate one' AI video generator is capable of producing videos with a resolution of 1024 by 576, which is considered high definition in the context of open-source text-to-video models.
How does the 'potate one' model compare to Runway ML's Gen 2 in terms of accessibility?
-While Runway ML's Gen 2 is a high-quality AI video generator, it is not open-source and has limited accessibility. In contrast, 'potate one' is fully open-source and can be accessed and modified by anyone, making it more accessible to the public.
What is the potential of open-source software in the context of AI video generation?
-Open-source software in AI video generation allows for community-driven improvements, modifications, and innovation. It enables a wider range of users to contribute to the development, leading to faster advancements and a more diverse range of applications.
What is the role of the Lambda API in the 'potate one' AI video generator?
-The Lambda API plays a role in the 'potate one' AI video generator by providing an interface for users to interact with the model and generate videos. It is one of the components that help facilitate the video creation process.
How long are the videos generated by the 'potate one' model?
-The 'potate one' model is currently capable of generating videos that are about a second long, though it is possible to generate longer videos by adjusting the number of frames.
What is the GPU requirement for running the 'potate one' model locally?
-The 'potate one' model can be run locally with a GPU that has over 15 gigabytes of VRAM, such as an Nvidia RTX 4080. For those using Google Colab, 15 gigs of RAM is supplied.
What is the process for generating a video using the 'potate one' model on Google Colab?
-To generate a video using 'potate one' on Google Colab, one must first run the setup cell to install the necessary packages and AI model. Then, input a prompt and run the generation cell, which will produce the video over time, depending on the complexity and length of the video.
What are some of the sample prompts used to test the 'potate one' AI video generator?
-Sample prompts used in the transcript include 'lemon character dancing on the beach bokeh', 'astronaut jumping through a world of fuzzy little blobs', and 'dog wearing a superhero outfit with a red cape flying through the sky'.
How can users get involved with the 'potate one' project and share their creations?
-Users can get involved with the 'potate one' project by accessing the GitHub repository, running the model on their own machines or using Google Colab, and sharing their creations on the project's Discord server.
Outlines
🚀 Introduction to AI Video Generation
The script introduces the emerging field of AI video generation as the next step in AI technology, following the popularity of AI text and image generation. It highlights Google's high-resolution AI video and RunwayML's Gen 2, a multi-modal system for generating videos from various inputs. The main issue is the limited access to such technology, with Gen 2 being the most accessible but still not widely available. The script then introduces 'potate one', an open-source alternative to Gen 2, capable of generating higher resolution and frame rate videos, which is a significant development in the field of AI video generation.
🌟 Showcase of Open-Source AI Video Generator 'Potato One'
This paragraph showcases the capabilities of 'Potato One', an open-source text-to-video model that can generate higher resolution videos than Gen 2. It discusses the model's origins from Model Scope AI, its improvements in resolution and quality, and the availability of the training scripts. The script also provides examples of videos generated by 'Potato One', emphasizing the model's coherency and high-fidelity output. It mentions the model's requirements for running locally, such as 15GB of VRAM, and the potential for faster generation with personal GPUs or improved Google Colab setups.
🛠 Setting Up and Using 'Potato One' on Google Colab
The script provides a step-by-step guide on setting up and using 'Potato One' through Google Colab. It explains the process of installing the necessary requirements, inputting prompts, and generating videos. The paragraph also discusses the limitations of using Colab, such as long generation times, and suggests ways to potentially speed up the process, like adjusting the number of steps per frame or using a personal GPU. Additionally, it invites viewers to share their creations and offers to create a tutorial for local installation if there is enough interest.
🎨 Integration of 'Potato One' with Blender and Future Prospects
The final paragraph discusses the integration of 'Potato One' with Blender, thanks to the work of tintawton, making it easier for users to incorporate AI video generation into their workflows. It also mentions the upcoming 'Potato 2', which is expected to offer further improvements in video generation. The script concludes by expressing excitement about the open-source nature of 'Potato One' and its potential for future development, inviting viewers to share their thoughts on the technology and to look forward to the next AI news recap.
Mindmap
Keywords
💡AI Video Generation
💡Open Source
💡Text-to-Image Generation
💡Model Scope
💡Gen 2
💡Coherency
💡Resolution
💡Frame Rate
💡GitHub
💡Discord Server
💡VRAM
Highlights
Introduction of a new open-source AI video generator, a significant development in the field of AI.
AI text generation and manipulation are currently leading the AI field, with chat GBT being the most popular form.
Text-to-image generation is the second most popular form of generative AI, with tools like DALL-E and Bing.
AI video generation is the next step in AI image generation, with Google's Imogen video being a notable example.
Runway ML's Gen 2 is currently the most accessible AI video generator but has limitations in accessibility and open-source nature.
Announcement of 'Potato One', the first high-resolution, open-source text-to-video model.
Potato One is based on Model Scope AI video generator, offering higher resolution and frame rate than Gen 2.
Open-source software allows for modification and enhancement of video generators by the community.
Potato One generates videos at 1024x576 resolution, a significant leap into HD territory for open-source models.
The model still retains watermarks occasionally, a trait inherited from Model Scope.
Potato One is competitive with Gen 2, offering higher frame rate and resolution in video generation.
Demo videos showcase the potential of Potato One, including 3D animated fruits and coherent motion.
GitHub link provided for those interested in trying Potato One, with training scripts available for modification.
Potato 2 is in development, promising an even higher resolution and more coherent video generation.
The video generation process is slow, especially when using Google Colab, but offers high-quality results.
Users can run Potato One on their own machines if they have a GPU with over 15 gigabytes of VRAM.
Integration of Potato One into Blender is possible, offering an easier alternative to local Python installation.
The community is encouraged to share their creations using Potato One, fostering further development and innovation.
The video concludes with a discussion on the importance of open-source models and the potential of Potato One and its successor.