In the latest news update on August 11, Nvidia collaborated with the Israel Institute of Technology, Bar-Ilan University, and Simon Fraser University to publish a technical paper introducing the CALM AI model.
CALM, short for Conditional Adversarial Latent Models, is a sophisticated framework developed by Nvidia specifically for training customized virtual characters.
According to Nvidia, the training duration in the real world required for CALM is remarkably efficient, with just 10 days equivalent to a decade of training in a simulated environment.
Once trained, the CALM AI model exhibits an impressive capability to simulate a wide range of human actions, encompassing activities such as walking, standing, sitting, running, engaging in sword fights, and more.
Nvidia highlights that CALM excels in capturing the intricate complexity and diverse nature of human motion, enabling users to have direct control over their virtual characters’ movements.
The results of the research indicate that CALM effectively learns semantic motion representations, empowering higher-level task training for regulating generated motion and controlling the style. With additional training, users can manipulate their characters using a user-friendly interface akin to those found in popular video games.
For those interested in delving deeper into NVIDIA CALM, we have provided the official introduction page and GitHub page. Feel free to explore these resources to gain a more comprehensive understanding of this groundbreaking AI model.
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