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fractastical/README.md

Joel Dietz

Applied AI Researcher · Systems Architect · Founder

I build tools and research programs at the edge of AI, bioelectricity, machine consciousness, collective intelligence, and computational governance.

My work focuses on a simple question:

How do intelligent systems emerge, coordinate, adapt, and scale — across minds, machines, cells, markets, and institutions?

I am especially interested in systems that move from theory into implementation: simulations, agent architectures, research tooling, knowledge graphs, governance protocols, and experimental interfaces for new forms of intelligence.


Current Work

  • Machine consciousness
    Active inference, self-modeling agents, artificial sentience, computational phenomenology

  • Bioelectricity & morphogenesis
    Bioelectric signaling, regenerative systems, cellular intelligence, programmable form

  • Collective intelligence
    Coordination systems, governance protocols, decentralized institutions, group cognition

  • Computational creativity
    Generative systems, digital art, symbolic tools, creative AI workflows

  • Complex systems simulation
    Social, economic, biological, and institutional modeling


Selected Projects

Project Description
CIMC Philosophy Review Research publication focused on machine consciousness, active inference, and philosophy of mind
Bioelectricity Nexus Research network and knowledge hub for bioelectricity, morphogenesis, and regenerative biology
distributed-governance Definitions, bibliographies, and research notes on governance, blockchains, law, and coordination
Etherea Speculative systems project exploring Ethereum, Mars, AI, multiverses, and future civilization design
EtherCasts Early Ethereum education and smart-contract ecosystem work

What I Build

I am interested in projects that require both technical implementation and conceptual depth:

  • AI research tools
  • Agent systems and cognitive architectures
  • Scientific knowledge graphs
  • Bioelectricity and morphogenesis research infrastructure
  • Governance and coordination protocols
  • Simulation environments
  • Generative art systems
  • Research publications and technical strategy

Why This Matters

The next generation of AI will not only be about larger models.

It will involve systems that can:

  • model themselves
  • coordinate with other agents
  • integrate biological and computational intelligence
  • reason across scientific domains
  • participate in governance and collective decision-making
  • generate new structures, interfaces, and institutions

That is the frontier I work on.


Available For

I selectively collaborate on:

  • AI research consulting
  • machine consciousness and agent architecture projects
  • bioelectricity / morphogenesis research initiatives
  • computational governance systems
  • complex systems modeling
  • technical writing and research synthesis
  • talks, workshops, and advisory work

Links

Google Scholar ORCID Website X @jdietz X @fractastical


Fractals, agents, morphogenesis, governance, artificial life, and consciousness.

Pinned Loading

  1. morpholib morpholib Public

    Morphospace library produced as a collaboration between Allen Discovery Center at Tufts University and California Institute of Machine Consciousness

    Python 3

  2. distributed-governance distributed-governance Public

    Definitions and bibliographies for governance, blockchains, law, and consciousness

    TeX 59 13

  3. jQuery-for-Salesforce jQuery-for-Salesforce Public

    Set of scripts and classes that implement jQuery UI and other jQuery plugins with native Salesforce bindings

    18 11

  4. Hacker-News-Filter Hacker-News-Filter Public

    Chrome extension that provides filter for hacker news on karma score and keywords

    JavaScript 10 3

  5. hypermuse hypermuse Public

    Deterministic visual scoring system including audio reactive VJing software based on higher order math

    JavaScript 3

  6. bioinformatics-eval bioinformatics-eval Public

    AI-powered bioinformatics paper evaluator — evidence-first multi-agent pipeline scoring data transparency, dataset resolvability, code availability, and computational reproducibility.

    TypeScript