embedding-sharing LLM-economies

posted on 2025-01-02 by mhueschen (mostly written by ChatGPT)

Imagine a world where local communities, or collectives, manage their resources and energy flows autonomously, guided by shared values and cultural priorities. In this vision, technology doesn’t dominate; it empowers. Large Language Models (LLMs) become the cooperative tools of a post-capitalist society, enabling coordination without markets, competition, or exploitation.

The Problem with Today’s Systems

Global economic systems often reduce communities to abstract units in a market, prioritizing profit over people and the planet. This erodes local autonomy and homogenizes culture. Coordination between communities happens through markets or centralized bureaucracies—systems ill-suited to fostering equity and sustainability.

Enter LLM-Based Local Economies

What if every collective had its own AI-powered system to manage its “local economy”? An LLM tailored to their values, culture, and needs could:

  • Track resources like food, energy, and materials.
  • Help balance sustainability with the well-being of the community.
  • Suggest equitable ways to share surpluses or meet shortages.

This is not some top-down AI dystopia. These systems would work collaboratively with human decision-makers, acting as facilitators and record-keepers rather than authoritarian managers.

Coordination Without Markets

As collectives grow and interact, they need a way to “speak the same language” while respecting their differences. This is where cutting-edge AI techniques like shared embedding spaces come into play. Collectives can exchange information through aligned representations, enabling them to:

  • Understand each other’s needs and surpluses.
  • Coordinate directly without relying on price signals or monetary transactions.
  • Respect local cultures while forming networks of solidarity.

It’s like having a universal translator for economies—one that works on principles of cooperation rather than competition.

Federation Without Homogenization

This approach allows for lateral growth. Collectives can join federations where:

  • Each maintains its autonomy and cultural identity.
  • Shared AI systems align their resource flows for mutual benefit.
  • Coordination scales naturally, without centralized control.

This is a vision of growth through connection, not conquest.

How We Start

Building such a system starts small:

  1. Prototype Local Systems: Using open-source AI, we can simulate resource flows and decision-making in a hypothetical collective.
  2. Simulate Coordination: Experiment with how two or more collectives might align their economic activity without imposing one’s values on the other.
  3. Scale Thoughtfully: Gradually integrate these systems into real-world cooperatives, learning from their unique needs and priorities.

Why It Matters

This vision isn’t just about technology; it’s about transforming the way we live and work together. It’s a move away from systems that commodify everything toward ones that prioritize care, equity, and sustainability. By blending cutting-edge AI with timeless values of cooperation and mutual aid, we can imagine—and build—a world beyond capitalism.