Meta FAIR's AI research is guided by four core principles: openness, collaboration, excellence, and scale2. These principles underpin their commitment to fostering innovation and responsible development in the field of AI. By adhering to these principles, Meta FAIR aims to advance the state of the art in AI through open research, collaboration with the global AI community, maintaining high standards of excellence, and leveraging the power of scale to drive progress24.
JASCO (Joint Audio and Symbolic Conditioning for Temporally Controlled Text-to-Music Generation) improves control over text-to-music generation by accepting various conditioning inputs, such as specific chords or beats. This allows users to have more versatile and precise control over the generated music. JASCO applies information bottleneck layers in conjunction with temporal blurring to extract relevant information with respect to specific controls. This innovative approach enables JASCO to incorporate both symbolic and audio-based conditions in the same text-to-music generation model, resulting in higher quality and more controllable music generation.
The Meta Chameleon model family differs from traditional AI models by integrating text and images as inputs and outputs using a unified architecture. This approach, which employs tokenization for text and images, allows for a more streamlined and scalable method compared to traditional models that rely on diffusion-based learning. Chameleon can process and deliver both image and text simultaneously, enabling it to understand and generate content that seamlessly integrates both elements5. This capability opens up possibilities such as generating creative captions for images or combining text prompts and images to create new scenes.