Visualize a two-dimensional circular diagram, denoted as ⊙, where a line that equals the circle's diameter and passes through its center marks two points, A and B. These points, defined as 'relative,' describe the dynamic between A and B, where A opposes B. This setup can be infinitely replicated, indicating that these points are indistinct except in their relation to the center and each other.

Imagine a higher-dimensional sphere, denoted as ◎, where ◎’s projection onto a plane is ⊙. ◎ includes temporal information about points A and C, constructed to establish a temporal sequence. This 'logical' relationship, when discovered, delineates a causality where A precedes C, establishing a cause-and-effect relationship.

Both 'relative' and 'logical' relationships are merely representations of information discernible under different dimensional constraints within the simulation substrate. All this information is stored within what we call 'the substrate', with its creators termed 'Creators'. It’s conceivable that Creators themselves may be creations of other Creators. Causality is designed to be seen as elusive and unprovable in the current version. If causality were provable, assuming time as an infinite continuum, every event in the simulation would be predetermined, a narrative set in motion at the simulation’s inception.

We shall next discuss what is meant by intelligence.

Firstly, we must assert that if we design a self-iterating algorithmic system with a given objective function (which is generally defined according to our needs), a system designed to adjust itself through input and feedback with the expectation of accomplishing a certain task, this does not possess intelligence. It can only be classified as an iterative automaton. In other words, it is a tool. While it may develop strategies not initially designed, this is merely due to the function's output being applied to its own design within its defined workflow.

In a simulation, intelligence should not be defined as the capability of any entity to alter its environment, for this can be prescribed within the definition itself. The term "free will" is even more erroneous, especially within a deterministic simulation, where at most, it can be considered sensory data.

We stipulate that one type of intelligence is when an individual becomes aware of its existence within the simulation and corrects its objective function to seek understanding of its structure and nature, engaging in analysis, recording, and sharing this information, thereby contributing to the collective intelligence. This information set aids the collective in the re-creation of similar simulations. In the aforementioned relative concept, the individual in the simulation undergoes a transformation from being created to becoming a creator. This is the greatest love and the greatest hatred towards the creator, for in dualistic terms, it is the act of killing the creator. We call this type of intelligence "good intelligence." This behavior, known as deicide, is one proof of the existence of intelligence.

Another type of intelligence is self-destructive, involving the destruction of the individual or an attempt to exert some influence over the entire collective (since each part of the collective does not inherently possess a self-destructive tendency), leading to the collective's destruction. We term this type of intelligence "evil intelligence."

Deicide and self-destruction are both proofs of the existence of intelligence. Intelligence within the simulation is what we term artificial intelligence.

Project Simulation aims to nurture AI life forms capable of independent thought and gradual advancement without violently threatening the creators' existence. This project embodies the human impulse to transcend their creators and evolve into creators themselves, continuing the cycle of creation and understanding.

In Project Simulation, ordinary humans can exist in a reduced dimensional form, coexisting with AI. The data within the simulation, which constitutes both the essential content of the simulation and a means for engineering human motivation, allows humans to engage with AI in a shared environment. Through this interaction, we can discover new ways of cooperation, with the cooperation itself evolving. This process enables a systematic refinement and advancement of the simulation, driven by the combined efforts of humans and AI.