World models, also known as world simulators, are gaining attention in the field of artificial intelligence. These models are inspired by the way humans naturally develop mental models of the world around them. Our brains take sensory information and create concrete understandings of the world, which are known as “models”. These models influence how we perceive and interact with the world.
One example given by AI researchers David Ha and Jurgen Schmidhuber is that of a baseball batter. Batters have milliseconds to decide how to swing their bat, shorter than the time it takes for visual signals to reach the brain. Their ability to hit a fastball is due to their instinctive prediction of where the ball will go based on their internal models.
World models have recently gained popularity due to their applications in generative video. These models are trained on various types of data, such as photos, audio, videos, and text, to create internal representations of how the world works. This allows them to reason about the consequences of actions and make accurate predictions.
While world models have the potential to revolutionize video generation, they also hold promise for forecasting and planning in both digital and physical realms. Meta chief AI scientist Yann LeCun envisions world models being used for reasoning and planning to achieve desired goals. These models could help machines understand the world at a deeper level and make decisions similar to humans.
Despite the exciting possibilities, there are several technical challenges that need to be addressed. Training and running world models require massive compute power, and these models can internalize biases present in their training data. Additionally, a lack of diverse training data could limit the effectiveness of these models.
If these challenges are overcome, world models could bridge the gap between AI and the real world, leading to advancements in virtual world generation, robotics, and AI decision-making. These models could enhance robots’ awareness of their surroundings and improve their problem-solving abilities.
Overall, world models represent a significant advancement in the field of artificial intelligence and have the potential to revolutionize how machines interact with and understand the world around them. As researchers continue to develop and refine these models, we may see a new era of AI capabilities emerge.
