The First High Res FREE & Open Source AI Video Generator!

Summary

The video explores the emerging field of AI video generation, highlighting Google's Imogen and RunwayML's Gen 2. It introduces 'Potate One', an open-source, high-resolution text-to-video model surpassing Model Scope AI. With capabilities for 1024x576 resolution and potential for local GPU usage, Potate One offers a promising alternative to Gen 2, encouraging community-driven improvements and experimentation in AI video generation.

Takeaways

• 😀 AI text generation, like chatbots, is currently the most popular form of AI, followed closely by text-to-image generation and manipulation.
• 🌟 The next frontier in generative AI is AI video generation, with Google's Imogen video and Runway ML's Gen 2 being notable examples.
• 🚀 Runway ML's Gen 2 is a multi-modal system that can generate videos from text, images, or video clips, but it's not open source and has limited public access.
• 🌐 An open-source competitor to Gen 2 has emerged, called 'potate one', which is based on Model Scope AI video generator and offers higher frame rates and resolutions.
• 📹 'Potate one' is capable of generating 1024 by 576 resolution videos, marking a significant leap into HD territory for open-source text-to-video models.
• 💧 Despite the higher resolution, 'potate one' videos still sometimes include watermarks, similar to the base Model Scope videos.
• 🔗 The GitHub repository for 'potate one' is available, allowing users to run the model on their own machines and access training scripts.
• 🔄 'Potate 2' is in development, promising potentially higher resolution and more coherent video generation capabilities.
• 🎥 The video generation process with 'potate one' is slow, especially on Google Collab, but can be faster with better hardware or paid services.
• 🤖 The 'potate one' model shows promise in coherency and resolution, making it a strong open-source alternative to proprietary models like Gen 2.

Q & A

What are the two main types of AI that are currently popular?

The two main types of AI that are currently popular are AI text generation, such as chatbots, and text to image generation and manipulation.

What is the next level of AI image generation mentioned in the script?

The next level of AI image generation mentioned is AI video generation.

What is Google's contribution to AI video generation as mentioned in the script?

Google's contribution to AI video generation is an Imogen video, which is a high-resolution and high frame rate video.

What is Runway ML's Gen 2 and why is it significant?

Runway ML's Gen 2 is a multi-modal system that can generate novel videos from text, images, or video clips. It is significant because it is one of the few AI video generation tools that is accessible to the public.

Why is open-source software important in the context of AI video generation?

Open-source software is important because it allows for modification and building upon existing video generators, expanding the possibilities and improving the technology.

What is 'Potate One' and how does it relate to AI video generation?

'Potate One' is an open-source, 1024 by 576 text-to-video model announced by Kim Andrew. It is significant as it breaks into HD territory for open-source text-to-video models.

What are the main features of 'Potate One' that make it competitive with Runway ML's Gen 2?

Potate One is competitive with Runway ML's Gen 2 due to its higher frame rate, higher resolution video generation, and being fully open-source.

What is the significance of the model being able to generate videos with a resolution of 1024 by 576?

The significance is that it represents a step into HD territory for open-source text-to-video models, offering higher quality than previous models.

What is the role of the GitHub repository in the context of 'Potate One'?

The GitHub repository is where the source code and training scripts for 'Potate One' are available, allowing users to modify and improve the model.

How can users try out 'Potate One' without installing anything on their own machine?

Users can try out 'Potate One' for free using Google Colab, which provides a simple setup and allows the generation of videos without local installation.

What are some of the limitations or challenges mentioned in the script regarding AI video generation?

Some limitations or challenges include the generation time, which can be slow, and the complexity of setting up the model locally, which may require experience with installing GitHub repos and running Python.