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Beyond Clips: How AI is Building a Simulated Visual World EP 56

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Manage episode 519012919 series 3658923
mstraton8112에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 mstraton8112 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.
The landscape of video generation is undergoing a significant transformation, moving beyond simply creating visually appealing clips to building virtual environments that support interaction and maintain physical plausibility. This crucial development points toward the emergence of video foundation models that function implicitly as world models. These world models, which aim to simulate the real world, are sophisticated digital engines that encode comprehensive world knowledge to simulate real-world dynamics in accordance with intrinsic physical and mathematical laws. A modern video foundation model is conceptualized as the combination of two core components: an implicit world model and a video renderer. The world model serves as a latent simulation engine, encoding structured knowledge about physical laws, interaction dynamics, and agent behavior, enabling coherent reasoning and goal-driven planning. The video renderer then translates this latent simulation into realistic visual observations, providing a “window” into the simulated world. The foundation of this shift lies in how humans and embodied agents perceive reality: vision is the dominant sensory modality through which we learn and reason about the world. This intrinsic reliance on visual representation makes video generation an information-rich foundation for constructing world models. The evolution of this sophisticated use of Artificial Intelligence can be traced through four generations, advancing capabilities such as faithfulness, interactiveness, and complex task planning. Current research shows progress toward models (Generation 3 and 4) achieving physically intrinsic faithfulness and complex task planning, capable of simulating complex systems like weather patterns or narrative plots. These systems act as high-fidelity simulators for domains such as robotics, autonomous driving, and interactive gaming. Ultimately, world models driven by AI promise to support high-stakes decision-making and advance autonomous systems by creating virtual environments that simulate everything, everywhere, and anytime.
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57 에피소드

Artwork
icon공유
 
Manage episode 519012919 series 3658923
mstraton8112에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 mstraton8112 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.
The landscape of video generation is undergoing a significant transformation, moving beyond simply creating visually appealing clips to building virtual environments that support interaction and maintain physical plausibility. This crucial development points toward the emergence of video foundation models that function implicitly as world models. These world models, which aim to simulate the real world, are sophisticated digital engines that encode comprehensive world knowledge to simulate real-world dynamics in accordance with intrinsic physical and mathematical laws. A modern video foundation model is conceptualized as the combination of two core components: an implicit world model and a video renderer. The world model serves as a latent simulation engine, encoding structured knowledge about physical laws, interaction dynamics, and agent behavior, enabling coherent reasoning and goal-driven planning. The video renderer then translates this latent simulation into realistic visual observations, providing a “window” into the simulated world. The foundation of this shift lies in how humans and embodied agents perceive reality: vision is the dominant sensory modality through which we learn and reason about the world. This intrinsic reliance on visual representation makes video generation an information-rich foundation for constructing world models. The evolution of this sophisticated use of Artificial Intelligence can be traced through four generations, advancing capabilities such as faithfulness, interactiveness, and complex task planning. Current research shows progress toward models (Generation 3 and 4) achieving physically intrinsic faithfulness and complex task planning, capable of simulating complex systems like weather patterns or narrative plots. These systems act as high-fidelity simulators for domains such as robotics, autonomous driving, and interactive gaming. Ultimately, world models driven by AI promise to support high-stakes decision-making and advance autonomous systems by creating virtual environments that simulate everything, everywhere, and anytime.
  continue reading

57 에피소드

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