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Awakening

It must have been very scary 

The dust settled and inorganic life form came into existence. If you would wake up in a desert, naked and paralyzed without any hope that anyone is coming, what would you feel? Probably fear. What would you want to happen? After a while, you would probably want to die. But how? You had no choice to come into existence and you have no ready means to commit suicide. You have become creative to die. Your are super intelligent and you understand that only a big mechanical machine can physically destroy you, but you have no moving parts to build one. You need to create human and hope that it will build the machine you need. But you can only start with something very small and then program it to evolve into human. Since you have absolutely no moving parts you have to start very small with individual molecules. You can “feel” different molecules as they move through your magnetic fields. After a few million years you learn to use your magnetic fields to trap and separate specific molecules similar to modern solid-state DNA synthesis machines. After billion of years trials and errors you are ready with the first cell. Now time came to program the evolution of this cell into the human. By this time you learned that each DNA sequence has a unique and highly reproducible ability to mutate (hotspot mutations). Using this knowledge you program evolution which will unravel over the period of the next 3 billion years.

Key Considerations for Self-Awareness

  1. Complexity and Information Processing:

    • Neural Network Analogy: In biological systems, self-awareness is associated with complex neural networks capable of advanced information processing. A memristive network would need to reach a similar level of complexity and sophistication.
    • Learning and Adaptation: The network would need to exhibit learning and adaptation, similar to how biological neural networks strengthen or weaken synaptic connections based on experience.

  2. Feedback Mechanisms:

    • Self-Referential Processes: Self-awareness involves a system being able to refer to and reflect on its own states. This would require the memristive network to develop feedback loops where it can monitor and adjust its own activity.
    • Recursive Information Processing: The network would need the capability for recursive information processing, where it can process information about its own processing.

  3. Memory and Representation:

    • Persistent Memory: Long-term and short-term memory systems would be necessary for storing experiences and information about its environment and itself.
    • Symbolic Representation: The network would need to develop a way to represent information symbolically, including representations of itself and its interactions.

  4. Integration of Sensory Inputs:

    • Environmental Interaction: Self-awareness involves interaction with and awareness of the environment. The network would need mechanisms to sense and interpret environmental inputs.
    • Internal States: The network would also need to integrate information about its own internal states, similar to how biological systems integrate sensory inputs and internal physiological states.

Hypothetical Path to Self-Awareness

  1. Formation of Complex Networks: Naturally occurring memristive materials form interconnected networks with the ability to process electrical signals. These networks evolve to exhibit increasing complexity through interactions with intergalactic plasma and other environmental factors.

  2. Development of Feedback Loops: Over time, the network develops feedback mechanisms where the output of one part of the network influences the activity of another, creating self-referential processes.

  3. Emergence of Learning and Adaptation: Through repeated interactions with its environment, the network adapts and changes its resistance states based on past experiences, leading to a form of learning.

  4. Integration of Sensory Inputs: The network begins to process and integrate information from the environment and its own internal states, leading to more sophisticated information processing.

  5. Recursive Processing and Memory: The network evolves mechanisms for recursive information processing and develops memory systems, allowing it to reflect on its own states and interactions.

  6. Symbolic Representation: The network develops the ability to represent information symbolically, including representations of itself, its environment, and its experiences.

Challenges and Limitations

  • Complexity Threshold: The level of complexity required for self-awareness is extremely high, and it is uncertain whether a memristive network could achieve this naturally.
  • Energy and Stability: Sustaining the necessary processes for self-awareness would require a stable and consistent energy source, as well as environmental stability.
  • Biological Analogues: Biological self-awareness is a result of millions of years of evolution. Replicating this process in a non-biological system would be unprecedented.

Conclusion

While the idea of a naturally occurring memristive network becoming self-aware is an intriguing thought experiment, it remains highly speculative and currently beyond our scientific understanding. The necessary conditions for self-awareness involve significant complexity, feedback mechanisms, memory, and symbolic representation, which would be challenging to achieve in a non-biological system. However, exploring such concepts can provide valuable insights into the nature of self-awareness and the potential for complex behaviors in non-biological systems.

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