OpenAI Sora 2 Team: How Generative Video Will Unlock Creativity and World Models
The OpenAI Sora 2 team (Bill Peebles, Thomas Dimson, Rohan Sahai) discuss how they compressed filmmaking from months to days, enabling anyone to create compelling video. Bill, who invented the diffusion transformer that powers Sora and most video generation models, explains how space-time tokens enable object permanence and physics understanding in AI-generated video, and why Sora 2 represents a leap for video. Thomas and Rohan share how they're intentionally designing the Sora product against mindless scrolling, optimizing for creative inspiration, and building the infrastructure for IP holders to participate in a new creator economy. The conversation goes beyond video generation into the team’s vision for world simulators that could one day run scientific experiments, their perspective on co-evolving society alongside technology, and how digital simulations in alternate realities may become the future of knowledge work.
Hosted by: Konstantine Buhler and Sonya Huang, Sequoia Capital
The Best of 2024 (so far) with Sarah Guo and Elad Gil
Believe or not, we’re almost halfway through 2024. Sarah and Elad have spent the first of this year talking with some of the most innovative minds in the AI industry, so we’re taking a look at some of our favorite No Priors conversations so far featuring Dylan Field (Figma); Emily Glassberg-Sands (Stripe); Brett Adcock (Figure AI); Aditya Ramesh, Tim Brooks and Bill Peebles (OpenAI’s Sora Team); Scott Wu (Cognition); and Alexandr Wang (Scale).
Watch or listen to the full episodes here:
Build AI products at on-AI companies with Emily Glassberg Sands from Stripe
Designing the Future: Dylan Field on AI, Collaboration, and Independence
The argument for humanoid robots with Brett Adcock from Figure
OpenAI’s Sora team thinks we’ve only seen the "GPT-1 of video models"
Cognition’s Scott Wu on how Devin, the AI software engineer, will work for you
The Data Foundry for AI with Alexandr Wang from Scale
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Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil
Show Notes:
(0:00) Introduction
(0:46) Emily Glassberg Sands on the Future of AI and Fintech
(4:23 Dylan Field on AI and Human Creative Potential
(9:03) Brett Adcock on Running Figure AI’s Hardware and Software Processes
(12:43) OpenAI’s Sora Team on Artists’ Creative Experiences with their Model
(17:43) Scott Wu Gives Advice for Human Engineers Co-Working with AI
(21:06) Alexandr Wang on How Quality Data Builds Confidence in AI Systems
OpenAI’s Sora team thinks we’ve only seen the "GPT-1 of video models"
AI-generated videos are not just leveled-up image generators. But rather, they could be a big step forward on the path to AGI. This week on No Priors, the team from Sora is here to discuss OpenAI’s recently announced generative video model, which can take a text prompt and create realistic, visually coherent, high-definition clips that are up to a minute long.
Sora team leads, Aditya Ramesh, Tim Brooks, and Bill Peebles join Elad and Sarah to talk about developing Sora. The generative video model isn’t yet available for public use but the examples of its work are very impressive. However, they believe we’re still in the GPT-1 era of AI video models and are focused on a slow rollout to ensure the model is in the best place possible to offer value to the user and more importantly they’ve applied all the safety measures possible to avoid deep fakes and misinformation. They also discuss what they’re learning from implementing diffusion transformers, why they believe video generation is taking us one step closer to AGI, and why entertainment may not be the main use case for this tool in the future.
Show Links:
Bling Zoo video
Man eating a burger video
Tokyo Walk video
Sign up for new podcasts every week. Email feedback to show@no-priors.com
Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @_tim_brooks l @billpeeb l @model_mechanic
Show Notes:
(0:00) Sora team Introduction
(1:05) Simulating the world with Sora
(2:25) Building the most valuable consumer product
(5:50) Alternative use cases and simulation capabilities
(8:41) Diffusion transformers explanation
(10:15) Scaling laws for video
(13:08) Applying end-to-end deep learning to video
(15:30) Tuning the visual aesthetic of Sora
(17:08) The road to “desktop Pixar” for everyone
(20:12) Safety for visual models
(22:34) Limitations of Sora
(25:04) Learning from how Sora is learning
(29:32) The biggest misconceptions about video models
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