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Conviction and Conviction | Pod People에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Conviction and Conviction | Pod People 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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OpenAI’s Sora team thinks we’ve only seen the "GPT-1 of video models"

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Conviction and Conviction | Pod People에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Conviction and Conviction | Pod People 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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:

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

  continue reading

63 에피소드

Artwork
icon공유
 
Manage episode 414538843 series 3444082
Conviction and Conviction | Pod People에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Conviction and Conviction | Pod People 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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:

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

  continue reading

63 에피소드

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