Yoichi Ochiai: In our world, objects play a significant role in our understanding of the environment. By naming objects, such as mathematical equations, abstract concepts like friendship, or tangible things like desks, dogs, or even people like Honda-san, we create a world around us. However, when there's an abundance of objects, the relationships between them start to become vague, and this is something I've noticed with GPT-4.
Ken Endo: I've spent a month being deeply interested in how our body's knowledge about the world affects our understanding of it. However, most of our knowledge of the world is not entirely accurate. It's like someone who has only practiced swimming by reading books in a library - the experience doesn't quite match the reality. But, interestingly, when the experience is provided, our knowledge starts to fit better.
Yusuke Sugano: Language is a crucial aspect of our self-body perception. We recognize parts of our body, like fingers, as objects, but we don't necessarily think of them as objects when we move them. This gap between object recognition and actual movement is fascinating.
Tatsuya Honda: In our conversations, I sometimes worry if I fully understand the concept of "object." What exactly is an object, and how does it relate to object-oriented thinking? There's a phenomenon where we struggle with communication when we don't have a clear understanding of these concepts.
Yoichi Ochiai: I find Carl Sims' work fascinating because he heavily relies on object-oriented thinking. However, I believe that objects themselves are not necessarily aware of their own existence. The distance between the two is what intrigues me. In communication, objects might not be necessary, but they do help humans in recognition and understanding.
Ken Endo: In the field of natural language processing, especially in English, parsing can be done relatively easily by connecting objects through language. It might be why objects are convenient to use and why they have excellent compatibility with GPT-4.
Yusuke Sugano: When we first started working on the project, we didn't specifically aim to create a small language using objects. We continuously input Buddhist scriptures and attempted to minimize them using Python. However, when we incorporated neural networks, the text became object-oriented, and it resulted in some interesting findings.
Tatsuya Honda: GPT has a unique aspect where it seems to try to learn from reinforcement learning. When interacting with the interface, you can feel that the learning routine is constantly present, which is different from how things work in reality.
Yoichi Ochiai: In the real world, we understand the laws of physics, such as Newton's laws of motion and acceleration due to gravity. However, these laws are not always accurate since they depend on factors like the distance from the center of gravity and the effects of other objects. Energy absorption, for example, is not just about spring-dampers, but also involves sound and heat.
In summary, our understanding of the world is heavily influenced by the concept of objects and their relationships. The gap between object recognition and actual movement, as well as the compatibility between objects and natural language processing, are fascinating aspects of human cognition. GPT-4's learning process and its relationship with reinforcement learning also provide interesting insights into artificial intelligence and its differences from the real-world understanding of physics.