This Free AI Video Generator is Wild!

Matt Wolfe
28 Jun 202311:28

TLDRThe video introduces a groundbreaking text-to-video generation tool, Xeroscope, which has been made available for free on Hugging Face. The tool leverages AI to create short, watermark-free videos based on text prompts, demonstrating impressive results such as a robot cat with lasers and a celebration with fireworks. While the free version can have long generation times, the tool's potential is evident, offering a new dimension in content creation and showcasing the evolving capabilities of AI in video generation.


  • ๐ŸŒŸ A new text-to-video tool, Xeroscope, has been released and is generating a buzz for its wild video outputs.
  • ๐Ÿ” The tool uses a model called Panohead, which creates 3D heads from single images, as an example of its capabilities.
  • ๐Ÿ’ก Panohead is based on GAN (Generative Adversarial Network) technology, which refines its output by comparing and adjusting it to the original image.
  • ๐Ÿ“ธ The Panohead research is open source and available on GitHub, but requires high-end Nvidia GPUs to run efficiently.
  • ๐Ÿš€ Another research project mentioned is Motion GPT, which translates text descriptions of human motion into video animations.
  • ๐Ÿค– Motion GPT can also convert video motion to text and predict future movements, but it's not publicly accessible yet.
  • ๐Ÿ“ˆ The video compares Xeroscope with other text-to-video tools like RunwayML and Model Scope, highlighting the pros and cons of each.
  • ๐Ÿ†“ Xeroscope is available for free on Hugging Face, but the generation time can be long and it may be busy during peak hours.
  • ๐Ÿ’ป The recommended hardware for faster video generation with Xeroscope is an Nvidia A10 GPU, which can be rented for about $3.15 per hour.
  • ๐ŸŽจ Xeroscope has produced creative and visually appealing videos, such as a robot cat with lasers and a psychedelic celebration with fireworks.
  • ๐Ÿ”„ Users have found ways to extend video length by generating multiple short videos and combining them, showcasing the versatility of the tool.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is the introduction of a new text-to-video generation tool and its capabilities.

  • How does the Panohead research work?

    -Panohead is a research project that allows the creation of 3D heads based on a single image. It uses a Generative Adversarial Network (GAN) to refine the generated image until it closely resembles the original picture from various angles.

  • What does GAN stand for and what is its role in Panohead?

    -GAN stands for Generative Adversarial Network. In Panohead, it plays a crucial role by comparing the generated images with the original picture and making adjustments until the generated images closely match the original.

  • What is the Motion GPT human motion research about?

    -Motion GPT human motion research is about generating text emotions and converting them into motion or vice versa. It can generate descriptions of human movements and even predict the next movements based on the observed motion.

  • What are the two text-to-video generation tools mentioned in the video?

    -The two text-to-video generation tools mentioned are RunwayML and Model Scope on Hugging Face.

  • What is the issue with using Model Scope on Hugging Face?

    -The issue with using Model Scope on Hugging Face is that the generated videos have a watermark from Shutterstock across them, as the tool was likely trained on Shutterstock data.

  • What is Xeroscope and how does it differ from Model Scope?

    -Xeroscope is a new text-to-video generation tool available for free on Hugging Face. Unlike Model Scope, it does not have a watermark on the generated videos and produces slightly more coherent outputs.

  • What is the downside of using the free version of Xeroscope?

    -The downside of using the free version of Xeroscope is that the generation time can be fairly long, and during peak hours, the service might be too busy to generate videos.

  • How can one improve the video generation speed with Xeroscope?

    -One can improve the video generation speed by using an Nvidia A10 G, which reduces the generation time to less than a minute per video, allowing for a higher volume of videos to be created in a shorter period.

  • What are some examples of the types of videos generated with Xeroscope?

    -Examples of videos generated with Xeroscope include a robot cat with lasers, an underwater creature scenario, a celebration with fireworks, and a video of Elon Musk wrestling with Mark Zuckerberg.

  • How can one access and use Xeroscope?

    -Xeroscope can be accessed and used for free on Hugging Face. However, for faster generation, one can duplicate the space and use an Nvidia A10 G for a more efficient video creation process.



๐ŸŽฅ Introduction to Text-to-Video Tools and Panohead Research

The video begins by introducing a new text-to-video generation tool that has been recently made available, promising exciting results. The host plans to discuss various impressive generations and demonstrate how to use such tools freely. Before diving into the new text-to-video model, the video presents research on Panohead, an AI that creates 3D heads from single images. The technology utilizes GAN (Generative Adversarial Network) to refine the generated images to closely resemble the original. The Panohead research is open-source and available on GitHub, but it requires high-end GPUs to run. The video also mentions another research project, Motion GPT, which generates human motion from text descriptions and predicts further movements, though it is not yet publicly accessible.


๐Ÿ“น Text-to-Video Generation Tools and Zeroscope

The paragraph discusses various platforms for text-to-video generation, including RunwayML and Model Scope, with the latter having a watermark due to its training on Shutterstock data. The host introduces Xeroscope, a new tool available for free on Hugging Face, which removes the watermark and improves coherence in the generated videos. However, the free version of Xeroscope can be slow and may not work during peak hours. The host shares several examples of creative videos generated using Xeroscope, highlighting its capabilities and potential for viral content creation. Xeroscope can be used for free on Hugging Face, but the host notes that a paid, faster version is also available by duplicating the space, which allows for quicker video generation.


๐Ÿš€ Conclusion and Resources for AI Tools and News

In the concluding paragraph, the host wraps up the discussion on the new text-to-video AI tool, Zeroscope, emphasizing its free availability and potential for creating entertaining videos. The host encourages viewers to explore more examples on Twitter and suggests visiting for the latest AI tools and news. Additionally, the host invites viewers to join a free newsletter for a weekly roundup of AI developments and to engage with the content by liking the video, subscribing, and turning on notifications for more similar content.



๐Ÿ’กText to Video Generation

Text to video generation refers to the process of converting written text into a video format using artificial intelligence. In the context of the video, this technology has recently advanced to create realistic and engaging video content based on textual descriptions, setting a new standard for what can be achieved with text-to-video conversion tools.


Panohead is a term used in the video to describe a research project that allows the creation of 3D heads from a single image. This technology uses Generative Adversarial Networks (GANs) to generate a 3D model that can be rotated and viewed from different angles. It is an example of how AI can be used to create realistic and detailed visual content from limited input.

๐Ÿ’กGenerative Adversarial Networks (GANs)

Generative Adversarial Networks, or GANs, are a type of AI model used for unsupervised learning. They consist of two parts: the generator, which creates new data, and the discriminator, which evaluates the generator's output. GANs are used in various applications, including image and video generation, where they can produce highly realistic results by learning from a large dataset.


GitHub is a web-based platform that provides version control and collaboration features for software developers. It is a repository where developers can store their code, share it with others, and collaborate on projects. In the context of the video, GitHub is mentioned as the platform where the open-source research for Panohead is available for those interested in exploring or utilizing it.

๐Ÿ’กMotion GPT

Motion GPT, as mentioned in the video, is a research project focused on human motion that can generate text descriptions of movements and convert them into motion. This technology can be used to understand and predict human actions, and it has potential applications in areas such as animation, gaming, and virtual reality.


RunwayML is a platform that provides machine learning tools for creators to generate visual content. It offers a suite of tools that can be used to create text-to-video content, among other functionalities. In the video, the speaker mentions using RunwayML for text-to-video generation, noting that it produces good results but can be costly in terms of credits used for video generation.

๐Ÿ’กModel Scope

Model Scope is a tool available on Hugging Face that allows users to generate videos for free. However, the videos generated through this tool often have a watermark, indicating that the content was created using the Model Scope platform. The video discusses the limitations of Model Scope in terms of the watermark and the quality of the generated videos.


Xeroscope is a text-to-video AI tool that has been recently made available for free on Hugging Face. It is capable of generating short, coherent videos without watermarks, offering a more polished output compared to some other free tools. However, the generation process can be slow, and the tool may become unavailable during peak usage times.

๐Ÿ’กHugging Face

Hugging Face is an open-source platform that provides a variety of AI models, including text-to-video generation tools like Model Scope and Xeroscope. It allows users to access and utilize these models for different applications, often for free or at a low cost.

๐Ÿ’กAI-generated Videos

AI-generated videos are those created by artificial intelligence without human intervention. These videos can range from simple animations to complex, realistic scenes, depending on the sophistication of the AI model used. The video discusses the capabilities of various AI tools in generating such content, highlighting the advancements and potential of this technology.

๐Ÿ’กAI Developments

AI developments refer to the ongoing advancements and innovations in artificial intelligence technology. These can include improvements in machine learning algorithms, new applications of AI in various fields, and the creation of more sophisticated AI models. The video focuses on recent AI developments in the area of text-to-video generation, emphasizing the rapid progress in this field.


A new text-to-video generation tool has been released, setting a new standard for what text-to-video can achieve.

The tool allows users to create videos for free, making it accessible to a wider audience.

Panohead is a research project that generates 3D heads from a single image, using GAN (Generative Adversarial Network) technology.

The 3D generated heads can be rotated and viewed from different angles, although the accuracy may not be perfect.

Motion GPT is another research project that translates text into human motion, and can also predict the next movements.

Motion GPT can convert text descriptions into motion, such as a person practicing karate kicks, and generate corresponding text emotions.

Panohead is open-source and available on GitHub, but requires high-end Nvidia GPUs to run.

There is currently no public cloud version of Panohead, but it is expected to become available soon.

Text-to-video generation was previously limited to platforms like RunwayML and Model Scope, which had their own drawbacks.

Xeroscope is a new text-to-video tool available for free on Hugging Face, without the watermark present in Model Scope videos.

Xeroscope can generate videos quickly, but the generation time can be long during peak hours and it may become unavailable due to high demand.

The recommended hardware for Xeroscope is an Nvidia A10 G, which costs about $3.15 per hour, allowing for the theoretical generation of 50 to 60 videos per hour.

Showcases of Xeroscope's capabilities include a robot cat with lasers, a colorful underwater scene, and a celebration with fireworks.

Xeroscope's generated videos are being shared widely on social media platforms, demonstrating the AI's ability to create visually appealing content.

The video provides a demonstration of generating a monkey on roller skates using Xeroscope within Hugging Face, with a cartoony style.

The video also shows how to recreate a swimming octopus in a vibrant blue ocean using Xeroscope, with an estimated generation time of 51 seconds.

A humorous example of the tool's capabilities is a video depicting Elon Musk wrestling with Mark Zuckerberg.

The video concludes by highlighting the fun and creativity involved in using AI-generated video tools like Xeroscope.