From Imitation to Understanding: Will Artificial Intelligence Build Its Own Model of the World?

Artificial intelligence has come a long way from simple algorithms to advanced models like LLMs (Large Language Models). These impressive tools can generate texts, images, and even code, which are increasingly difficult to distinguish from those created by humans. But does this mean that AI truly "understands" the world it describes?

Imitation at a Higher Level – Mimicking the Thought Process

Currently, LLMs not only imitate the result but also mimic the process of reaching that result. Through techniques like "Chain-of-Thought prompting," models can generate intermediate reasoning steps, giving the illusion of deeper understanding. It's like watching a model "think aloud." However, we are still talking about imitation, though at a much higher level – mimicking the human way of thinking and reasoning.

The Dream of the "World Model" – A Challenge for AI

For AI to truly understand the world, it would need something more than just advanced imitation – it would need a model of the world. What would such a model look like? Primarily, it would be a structure that contains representations of:

• Objects and their properties, relationships between them, physical laws, knowledge about the world, and ultimately – abstract concepts.

This is an ambitious task because the world is incredibly complex, and fully describing it is a huge challenge. How can we represent knowledge in a way that AI can understand? How can we model abstractions? What about constant changes and the need to continuously update the "world model"?

Attempts to Build a "World Model" – Current Research Directions

Despite the difficulties, researchers are actively working on creating a "world model" for AI, using various approaches:

• Knowledge Bases: Developing large, structured knowledge systems like WordNet, Cyc, and Wikidata.
• Knowledge Graphs: Representing knowledge in the form of graphs, where objects are nodes and relationships between them are edges.
• Symbolic Representations: Integrating AI systems with symbolic logic and reasoning systems.
• Rule-based Systems: Creating systems that use logical rules to represent knowledge.
• Learning in Simulations: Training AI in simulated environments so it can build its own "world model" through interaction.
• Multimodal AI: Integrating data from various sources (text, image, sound) to create a more holistic representation of the world.

Our World Model – Awareness, Experience, and Continuous Update

When analyzing attempts to build a "world model" for AI, it is impossible not to look at our own, human way of understanding the world. Our internal world model is built based on our experiences, senses, emotions, and interactions with the environment. Importantly, we are constantly updating it, learning new things, verifying beliefs, and adapting to changes. Our consciousness allows us to introspect and reflect, enabling us to modify our model based on reasoning and analysis. This model also includes knowledge about ourselves, other people, and abstract concepts. It is our consciousness that enables us to dynamically build, modify, and navigate reality.

Similarities and Differences: AI and the Human World Model

Both we and AI aim to create a representation of the world that allows us to act and predict the future. The difference lies in the fact that our "world model" is based on consciousness, emotions, experience, introspection, and is subjective, while current attempts to build this model for AI are based on data analysis, rules, and logic. Our model continuously updates itself through interaction with the world, while AI still faces significant challenges in this area.

The Future: From Imitation to True Understanding

Will AI ever reach the level of human understanding? We do not know the answer. Today's attempts to build a "world model" for AI are just the first steps. However, we can still learn from our way of understanding the world and draw inspiration from human consciousness in the search for new solutions.

Perhaps future AI, based on the "world model," will not only be a master of imitation but a true partner in discovering and understanding our universe.