Text to Video: The Next Leap in AI Generation

This podcast episode discusses the challenges and innovations in text-to-video models, as well as the advancements and benefits of diffusion models for language and image generation. The speakers prioritize stable video generation and explore the unique aspects of video modeling compared to image modeling. They also discuss the potential of generative video modeling in understanding the physical properties of the world and integrating other modalities like language. Additionally, the episode highlights the effectiveness of fine-tuning a pre-trained video model on multi-view orbits around 3D objects and the future of video creation tools. The hosts share their excitement about the possibilities of video generation and emphasize the importance of infrastructure improvements to drive further innovation in this field. Finally, the impact of Stable Diffusion on AI research and the collaborative nature of the industry are explored. Takeaways • Stable Video Diffusion released by Stability AI is a state-of-the-art open-source generative video model that addresses the challenges in text-to-video techniques. • Diffusion models offer advantages such as gradual transformation process, ability to train on various noise levels and use fewer steps during sampling, resulting in improved quality and prompt following. • Video modeling includes additional temporal dimensions and allows models to generate camera pans, object movements, and even hallucinate how objects look from different angles. • Fine-tuning a pre-trained video model on multi-view orbits around 3D objects using lightweight adapters offers creative possibilities in video creation. • Infrastructure improvements are needed to generate longer and more coherent videos and overcome bottlenecks for faster and multimodal video generation. • Open-sourcing models like Stable Diffusion promote research and innovation, enabling accessibility to a wider community. • Collaboration and sharing in the AI industry are important for driving innovation and supporting the growth of research.