Key Takeaways:
- Researchers are working on creating "world models" to improve the performance of artificial intelligence (AI) systems, including video generation, chatbots, and autonomous vehicles.
- World models are internal representations of the world that can be updated in real-time, allowing AI systems to make more informed decisions.
- 4D modeling, which involves creating three-dimensional models that change over time, is a key component of world modeling.
- Advances in 4D modeling have the potential to improve the performance of AI systems in a range of applications, including augmented reality, robotics, and human-like intelligence.
- The development of world models is seen as a crucial step towards achieving artificial general intelligence (AGI).
Introduction to World Models
The concept of world models is not new, but recent advances in artificial intelligence (AI) have brought it to the forefront of research. A world model is an internal representation of the world that an AI system uses to make decisions and take actions. As Angjoo Kanazawa, an assistant professor of electrical engineering and computer sciences at the University of California, Berkeley, notes, "In a way, I would say that the LLM already has a very good world model; it’s just we don’t really understand how it’s doing it." However, current AI systems, including large language models (LLMs), do not have a real-time physical understanding of the world, and their ability to update their understanding of the world is limited.
The Limitations of Current AI Systems
Current AI systems, including those that power ChatGPT, have limitations when it comes to understanding the world. They are trained on large datasets, but they do not have the ability to update their understanding of the world in real-time. As Kanazawa notes, "How do you develop an intelligent LLM vision system that can actually have streaming input and update its understanding of the world and act accordingly? That’s a big open problem. I think AGI is not possible without actually solving this problem." This limitation is evident in the example of a video generation system that predicts what is statistically most plausible to look right next, rather than having a clear understanding of the world.
The Potential of 4D Modeling
4D modeling, which involves creating three-dimensional models that change over time, has the potential to improve the performance of AI systems. By creating 4D models of the world, AI systems can better understand the relationships between objects and how they change over time. This can be applied to a range of applications, including video generation, augmented reality, and robotics. As the authors of a recent preprint note, "TeleWorld: Towards Dynamic Multimodal Synthesis with a 4D World Model," applies to the scenario of a dog running behind a love seat, where the system’s 4D model would help to prevent the love seat from becoming a couch and the dog from losing its collar.
Applications of World Models
The applications of world models are numerous and varied. In augmented reality (AR), a 4D world model can provide an evolving map of the user’s world over time, allowing AR systems to keep virtual objects stable and make lighting and perspective believable. In robotics, 4D models can provide rich data for training robots on how the real world works, and can help robots navigate their environment and predict what might happen next. As Yann LeCun, a prominent AI researcher, notes, "To achieve occlusion, a 3D model of the physical environment is required." The development of world models is also seen as a crucial step towards achieving AGI, as it would provide a foundation for understanding how the world works and making decisions based on that understanding.
The Path to AGI
The development of world models is a key step towards achieving AGI. As LeCun notes, "The answer [to why humans can act well in situations they’ve never encountered] may lie in the ability… to learn world models, internal models of how the world works." Research increasingly shows the benefits of internal models, and advances in 4D modeling could provide components that help with understanding viewpoints, memory, and even short-term prediction. As Kanazawa notes, "I think AGI is not possible without actually solving this problem." The development of world models is an active area of research, with many prominent AI researchers working on creating systems that can understand the physical world, have persistent memory, and can reason and plan complex action sequences.
Conclusion
In conclusion, the development of world models is a crucial step towards achieving AGI and improving the performance of AI systems in a range of applications. 4D modeling is a key component of world modeling, and has the potential to provide rich simulations of reality in which to test AIs. As researchers continue to work on creating world models, we can expect to see significant advances in the field of AI, and a move towards more generalizable and human-like intelligence. As Kanazawa notes, "That’s a big open problem. I think AGI is not possible without actually solving this problem."
https://www.scientificamerican.com/article/world-models-could-unlock-the-next-revolution-in-artificial-intelligence/