World model

World model is an AI model that understands the principles of the physical world (gravity, space, causality). Robotics and video creation are considered the next step in AI.

A world model is not a language, but an AI model that internally understands the operating principles of the physical world, that is, how objects fall, collide, and are obscured, and predicts the next situation. Just as a person intuits where a ball will fall just by looking at him throwing a ball, it can be compared to AI drawing the next scene of the world using a simulator in the head.

The limitation of LLM, which is taught only through text, has been pointed out as being difficult to use for robots or autonomous driving due to its weak physical common sense. In an attempt to go beyond this, world models are attracting attention as a basis for allowing robots to simulate the results of their actions in advance or generate physically natural images, and are considered by several prominent researchers as the next step in AI.

However, it is a field where there is still a distance between research concept and actual implementation, and there is debate as to whether the plausible physical representation shown by image generating AI is a true understanding of the world.

✅ Why it matters

• Robots and autonomous driving become the basis for predicting the results of actions in advance
• Opening up new applications such as creating physically natural images
• These are key keywords for understanding the direction of AI development next to LLM

⚠️ Limits and debates

• It is still in the research stage and is far from being commercialized
• There is debate as to whether plausible predictions are a true understanding of physics
• Learning requires vast amounts of image data and computational resources