General Partner Anjney Midha explores the cutting-edge world of text-to-video AI with AI researchers Andreas Blattmann and Robin Rombach. Released in November, Stable Video Diffusion is their latest open-source generative video model, overcoming challenges in size and dynamic representation. In this episode Robin, and Andreas share why translating text to video is complex, the key role of datasets, current applications, and the future of video editing. Topics Covered: 00:00 - Text to Video: The Next Leap in AI Generation 02:41 - The Stable Diffusion backstory 04:35 - Diffusion vs autoregressive models 07:17 - The benefits of single step sampling 10:55 - Why generative video? 13:10 - Understanding physics through AI video 14:53 - The challenge of creating generative video 18:43 - Data set selection and training 21:24 - Structural consistency and 3D objects 23:51 - Incorporating LoRAs 28:47 - How should creators think about these tools? 31:41 - Open challenges in video generation 32:35 - Infrastructure challenges and future research Resources: Find Robin on Twitter: https://twitter.com/robrombach Find Andreas on Twitter: https://twitter.com/andi_blatt Find Anjney on Twitter: https://twitter.com/anjneymidha Stay Updated: Find a16z on Twitter: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Subscribe on your favorite podcast app: https://a16z.simplecast.com/ Follow our host: https://twitter.com/stephsmithio Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.