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The Rise of Generative Media: fal's Bet on Video, Infrastructure, and Speed

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Manage episode 523558181 series 3586723
Content provided by Sequoia Capital. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Sequoia Capital or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

fal is building the infrastructure layer for the generative media boom. In this episode, founders Gorkem Yurtseven, Burkay Gur, and Head of Engineering Batuhan Taskaya explain why video models present a completely different optimization problem than LLMs, one that is compute-bound, architecturally volatile, and changing every 30 days. They discuss how fal's tracing compiler, custom kernels, and globally distributed GPU fleet enable them to run more than 600 image and video models simultaneously, often faster than the labs that trained them. The team also shares what they’re seeing from the demand side: AI-native studios, personalized education, programmatic advertising, and early engagement from Hollywood. They argue that generative video is following a trajectory similar to early CGI—initial skepticism giving way to a new medium with its own workflows, aesthetics, and economic models.Hosted by Sonya Huang, Sequoia Capital

  continue reading

74 episodes

Artwork
iconShare
 
Manage episode 523558181 series 3586723
Content provided by Sequoia Capital. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Sequoia Capital or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

fal is building the infrastructure layer for the generative media boom. In this episode, founders Gorkem Yurtseven, Burkay Gur, and Head of Engineering Batuhan Taskaya explain why video models present a completely different optimization problem than LLMs, one that is compute-bound, architecturally volatile, and changing every 30 days. They discuss how fal's tracing compiler, custom kernels, and globally distributed GPU fleet enable them to run more than 600 image and video models simultaneously, often faster than the labs that trained them. The team also shares what they’re seeing from the demand side: AI-native studios, personalized education, programmatic advertising, and early engagement from Hollywood. They argue that generative video is following a trajectory similar to early CGI—initial skepticism giving way to a new medium with its own workflows, aesthetics, and economic models.Hosted by Sonya Huang, Sequoia Capital

  continue reading

74 episodes

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