Ethereum: A Model of the World
  • Down the Rabbit Hole
  • Part I
    • One Simple Idea
    • Entropy
    • Free Energy and Entropy
    • Variational Free Energy
    • Examples
    • Into the Ether
    • The World Modelling Computer
    • Modelling the World
    • The Economy of Neurotransmitters
    • A Distributed Ledger
    • Consensus at Scale
    • Concluding Remarks
  • Part II
    • Limbic Resonance Consensus Algorithm - Layer 0
  • About the Author
    • Pranav M. Jagtap, MD
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On this page
  • Modelling Modules
  • Patterns
  • Nature's Proof-of-Stake
  • Elasticity
  • Consensus?
  1. Part I

Concluding Remarks

PreviousConsensus at ScaleNextLimbic Resonance Consensus Algorithm - Layer 0

Last updated 3 years ago

This exploration attempted to show that there is a mathematical proof for demonstrating how everything is modeling everything around it, constrained by the parameters outlined in the Free Energy Principle. Ethereum appears to closely model (resemble) the most sophisticated world modelling computer we know of: the human brain (and nervous system).

Ethereum and the nervous system are both decentralized with their respective hardware and software. Because they are continuously updating their ledgers from moment to moment, and consequently their state of consensus, they can be more accurately characterized as . Both are distributed computing networks configured to model the world exceptionally well.

Modelling Modules

There are numerous modelling modules on Ethereum:

  • Prediction Markets (PolyMarket, Augur, Omen)

  • Decentralized Exchanges for organic price discovery (Uniswap, Sushiswap, Balancer)

  • Price discovery platforms for synthetic assets (Synthetix, Universal Market Access - UMA, Mirror Protocol)

  • Price discovery platforms for data markets (Ocean Protocol, Big Data Protocol)

  • Price discovery of Digital Gold (Wrapped Bitcoin)

  • Monetization of social media (NFTs, memes, social tokens, dog tokens, frog armies)

  • Healthcare markets (Soon - TM)

These dApps have been designed by some of the most brilliant minds in the world. Humans and Ethereum are modelling the same things.

Ethereum is the hivemind; Ethereum is a decentralized brain.

In addition to functional modelling denoted above (and in the ), the modelling is also structural. The striking resemblance between Merkle Trees and Dendritic Trees illustrates this relationship:

Patterns

An Attractor is a set of values towards which a bottom-up self-organizing and spontaneously organizing system may evolve. Examples include unemployment, inflation rate, Gwei prices.

Could this entail Free Energy minimization in the context of information entropy, economics, statistics, biology, chemistry, electronics - everything throughout the hierarchy of sciences? In other words, might Free Energy minimization correspond with game theoretically favorable outcomes/Schelling points?

Recall, John Nash (and the Nash Equilibrium) states: The best result will come when everybody in the group does what is best for themselves, and everybody else.

And this is indeed what we observe in the Ethereum ecosystem. Every person, and by extension each node, on Ethereum is incentivized to balance outcome maximization for oneself with the community at large. Decentralized Autonomous Organizations (DAOs), Ownership Economies, Gitcoin Grants, Public Goods, and the trailblazing proliferation of Decentralized Finance have all been a function of such incentive alignment promoting positive-sum games.

However, the system is not perfect and there are limitations:

Under Proof-of-Work, the system is exposed to gaping attack vector resulting in value extraction.

Nature's Proof-of-Stake

Fortunately, this will change after the network upgrades to Ethereum 2.0. We can consult Nature's Proof-of-Stake Consensus Algorithm for guidance and insights:

Under Proof-of-Stake, there are more incentives for value to be repurposed and remain within the system.

The legitimacy of Ethereum, especially after the network upgrade, will help the world transition from cancerous systems of the legacy world...

...to healthy and equitable networks for the world of tomorrow...

Instead of people working for systems, systems will work for the people.

Elasticity

Lastly a few thoughts on supply elastic tokens are warranted, given the considerable overlap between the two accounting systems (Neurotransmitters and ETH). The demand for most digital assets, by convention, is translated into its price; this is how the market values ETH, ERC-20 tokens, and other digital assets across blockchains. In contrast, the demand (or lack thereof) for Neurotransmitters is accommodated by a change in its supply.

Might supply elastic tokens hold the keys to fragile proofing the Decentralized Finance system?

Now that we live in a world driven by memes and narratives, it has become easy to buy into beliefs through Decentralized Finance. If there is any validity to these insights, then it behooves us to transform the knowledge into wisdom.

Consensus?

“Knowing is not enough, we must apply. Willing is not enough, we must do.”

-Bruce Lee

The journey down this rabbit hole could’ve continued because there are countless overlapping patterns. As the saying goes: history doesn't repeat itself, but it does rhyme. We are accustomed to think about this in terms of time, but it is also true with respect to space. This is exemplified by in , and more specifically through :

The Attractor above is a Strange Attractor; i.e. though it is recursive, it is not identically repeating unto itself. Contrast with :

These properties of chaotic systems can help us understand why there is considerable overlap across such systems. Governed by laws of physics, self-organizing and spontaneously ordering systems achieve equilibrium (and ) by minimizing (variational) Free Energy. It may be the case that this is best carried out when the work of Free Energy is efficiently distributed and allocated in accordance with Nash Equilibria and other game theoretically optimized outcomes.

Everything is inter-connected, and rhymes with Lindy ideas like .

Neurons that fire together also wire together, and neurons out of sync fail to link. This wiring is modulated by the change in quantity (supply) of neurotransmitters and synaptic receptors. It is strengthened primarily through mechanisms like , and weakened via (there are more other nuanced mechanisms for as well).

E.g.

Attractors
Complex Systems
Strange Attractors
Mandelbrot Set
non-equilibrium steady states
Indra’s Net
Long-term potentiation
Long-term depression
synaptic plasticity
Altered connectivity in Depression:
control systems
State Machines
Economy of Neurotransmitters