Soil ecoystem modeling is fundmentally about infinitely recursive neural networks

The SQL motto of Sequester C as life is about the superiority of dynamic LIVING systems … the neurology of life [on Earth, given the planet’s temperature regime] is fundamentally more dynamic, more adaptable, more evolveable than silicon-based intelligence.

It’s a matter of neurochemistry and why brains are NECESSARILY carbon-based, rather than silicon-based, ie it’s chemically-impossible to produce dynamic, adaptable, evolveable life without the neuroplasticity of carbon-based life. Thus, brains could only have evolved as being carbon-based rather than silicon-based, despite silicon having some very similar chemical properties to carbon.

Here’s the key gist of the reasoning:

  1. Temperature Regime:
  • Earth’s biosphere operates primarily between 0-40°C (with some extremophile exceptions)
  • This temperature range is crucial for liquid water and liquid water is essential for life, particularly evolving, adaptable life as we know it
  1. Carbon’s Properties at Earth Temperatures:
  • Carbon forms stable but flexible covalent bonds at Earth’s temperatures
  • Carbon compounds can readily form and break bonds in this temperature range
  • This allows for dynamic restructuring of neural connections (plasticity)
  • Carbon-based molecules can maintain complex 3D structures while still being modifiable
  1. Silicon’s Limitations at Earth Temperatures:
  • Silicon bonds are typically much stronger, more durable and less malleable than carbon bonds
  • Silicon compounds tend to be more rigid and less reactive at Earth temperatures
  • Silicon forms crystalline structures that are extremely stable but completely inflexible [on this planet]
  • Silicon chemistry typically requires much higher temperatures [than those found on Earth] to be dynamic
  1. Why This Matters for Brain Plasticity:
  • Learning and memory require constant physical restructuring of neural connections
  • Neurons need to form new connections and prune old ones
  • This requires molecular flexibility at Earth’s ambient temperatures
  • Carbon’s chemical properties allow this plasticity while maintaining structural stability
  1. Intelligence Requires Dynamic, Fluid, Evolveable Problem-Solving:
  • True intelligence requires handling novel, unpredictable situations
  • Static, pre-programmed responses can’t address the infinite variety of real-world challenges
  • Intelligence must be able to recognize patterns never before encountered
  • Must form new conceptual frameworks “on the fly”
  1. Learning as Physical Restructuring:
  • Each new understanding literally rewires neural pathways
  • Memories aren’t static “recordings” but dynamic reconstructions
  • Synaptic connections strengthen, weaken, form, and dissolve
  • Neural networks physically reorganize to encode new patterns and relationships
  • This requires molecular machinery that can:
    • Build new physical connections
    • Modify existing connections
    • Prune unnecessary connections
    • Do all this continuously throughout life
  1. Why Static Structures Are Insufficient:
  • Pre-wired circuits can only handle anticipated scenarios
  • Fixed memory structures can only store predetermined categories
  • Real intelligence requires:
    • Creating entirely new categories
    • Forming novel associations
    • Reorganizing existing knowledge structures
    • Abstracting new principles from experience
  1. The Role of Autodidacticism:
  • Self-directed learning requires physical self-modification
  • The system must be able to:
    • Evaluate its own performance
    • Identify knowledge gaps
    • Restructure itself to fill those gaps
    • Create new organizational schemes
  • This demands unprecedented physical plasticity
  1. Chemical Requirements:
  • The molecular machinery must be:
    • Stable enough to maintain long-term memories
    • Flexible enough for constant modification
    • Energetically efficient
    • Operational at biological temperatures
    • Capable of precise, controlled changes
  • Carbon chemistry uniquely satisfies these requirements at Earth temperatures
  1. Why Alternative Architectures Fall Short:
    • Crystal-based structures (like silicon) are too rigid
    • Pure electrical systems lack persistent physical remodeling
    • Digital memory is fundamentally binary and locationally fixed
    • Quantum systems are too unstable at biological temperatures

Conclusion

We aim to sequester C as LIFE in order to better develop the skills necessary for the fascinating exploration of the deep connection between intelligence and dynamism. It’s fundamentally important to understand the conclusions of this analysis, carefully, explicitly … at its most essential, inescapable, irrefutable manner. Dynamic intelligence requires a physical substrate that can continuously rewrite its own architecture. [In the temperature regime found on Earth] only carbon-based neurochemistry provides this capability in a way that other known chemical systems cannot, at least under Earth conditions.

Artificial intelligence systems, despite their power as tool for carbon-based life, will never overcome the superiority biological, carbon-based intelligence on Earth. Silicon-based computational system are incapable of mimicking the physical plasticity of biological neural networks. Their architecture, while reconfigurable in some minor, trivial, unimportant ways, can fundamentally never be dynamic. Since silicon-based AI can never physically restructure itself, it will always depend upon carbon based life adapt, evolve, re-configure and re-manufacture its learning structure.

The ONLY path to more advanced AI necessarily requires developing physically dynamic, LIVING computational substrates … this is why we sequester C as LIFE, rather than locking it away, deep underground, as elemental carbon or in an inert stable environment that preserves it indefinitely as carbon dioxide OR convert it into the high-grade, calcified mineral calcium carbonate known as limestone.