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What is VideoPoet?

VideoPoet is a groundbreaking modeling approach that enables any autoregressive language model or large language model (LLM) to function as a powerful video generator. This technique consists of several simple components. An autoregressive language model is trained to understand various modalities—including video, image, audio, and text—allowing it to predict the next video or audio token in a given sequence. The training structure for the LLM includes diverse multimodal generative learning objectives, which encompass tasks like text-to-video, text-to-image, image-to-video, video frame continuation, inpainting and outpainting of videos, video stylization, and video-to-audio conversion. Moreover, these tasks can be integrated to improve the model's zero-shot capabilities. This clear and effective methodology illustrates that language models can not only generate but also edit videos while maintaining impressive temporal coherence, highlighting their potential for sophisticated multimedia applications. Consequently, VideoPoet paves the way for a plethora of new opportunities in creative expression and automated content development, expanding the boundaries of how we produce and interact with digital media.

What is AudioCraft?

AudioCraft is a robust platform designed to fulfill all generative audio needs, which includes music, sound effects, and compression techniques honed through exposure to raw audio signals. By leveraging AudioCraft, we significantly improve the process of designing generative audio models, creating a more efficient solution compared to previous methods. MusicGen and AudioGen utilize a common autoregressive Language Model (LM) that operates on compressed discrete music representations, known as tokens. We introduce a clear approach that capitalizes on the internal organization of these parallel token streams, showing that with a single model and an advanced token interleaving strategy, our approach proficiently models audio sequences. This technique not only captures long-term dependencies inherent in the audio but also facilitates the generation of superior sound quality. Moreover, our models employ the EnCodec neural audio codec to convert raw waveforms into discrete audio tokens, with EnCodec transforming the audio signal into one or more parallel token streams. As a result, AudioCraft not only fosters advancements in audio generation but also effectively bridges the divide between high-quality output and operational efficiency in the realm of creative audio production. Furthermore, this integration of technology enhances the overall user experience, making the process more accessible for creators at all levels.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Google

Company Website

sites.research.google/videopoet/

Company Facts

Organization Name

Meta AI

Date Founded

2004

Company Location

United States

Company Website

audiocraft.metademolab.com

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