nostr-mind

Decentralized Collaborative Reasoning with Nostr

🚧 Work in Progress 🚧

We're building a decentralized, real-time system for collaborative reasoning using the Nostr protocol. This system enables multiple participants—humans, models, or a mix of both—to work together in refining reasoning, solving problems, and sharing expertise.

The goal is to create an open, censorship-resistant framework where:

• Thinkers (LLMs or humans) generate reasoning.
• Participants (Critics, domain experts, or other models) analyze, critique, and refine the reasoning.
• Open Collaboration: Anyone can join the network, contributing their unique expertise or data.

This is an open idea, and we're looking for contributors to help shape and build it!

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Why This Matters

In many domains, no single model or human has all the answers. By enabling open collaboration, we can:

• Leverage domain-specific expertise: Different models or humans may have access to private or specialized data, making their contributions invaluable.
• Improve reasoning quality: Multiple perspectives lead to better, more refined outputs.
• Ensure censorship resistance: Nostr's decentralized nature ensures no single entity can control or block the collaboration.

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Idea Overview

The system leverages Nostr's decentralized, pub/sub model to enable real-time communication between participants. Here's how it works:

1. Thinker generates reasoning and streams it to Nostr relays.
2. Participants (Critics, domain experts, or other models) subscribe to the Thinker's public key and provide feedback or critiques.
3. Thinker refines its reasoning based on feedback, creating an iterative improvement process.

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Key Features

1. Decentralized Collaboration:

   • Participants can join or leave the network at any time.
   • No central authority controls the flow of information.

2. Real-Time Feedback:

   • Thinkers pause and wait for feedback from Participants before proceeding.
   • Feedback is aggregated and used to refine reasoning.

3. Open Participation:

   • Anyone can contribute as a Participant, bringing their unique expertise or data.
   • Models with specialized fine-tuning or access to private data can provide domain-specific insights.

4. Censorship Resistance:

   • All interactions are signed and verifiable, ensuring transparency and trust.

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How It Works

Participants

1. Thinker: Generates initial reasoning (e.g., an LLM solving a problem).
2. Participants: Analyze, critique, or refine the Thinker's output. Participants can be:
   • Humans: Providing expert feedback.
   • Models: Offering domain-specific insights or alternative reasoning.
   • Hybrids: A mix of humans and models working together.

Workflow

1. Thinker publishes reasoning as Nostr events.
2. Participants subscribe to the Thinker's events and provide feedback.
3. Thinker pauses, aggregates feedback, and refines its reasoning.
4. Thinker publishes the refined reasoning and resumes the process.

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Example Use Case

Solving Linear Equations:

1. Thinker: "Step 1: Solve 3x + 5 = 20 → 3x = 15 → x = 5. Step 2: Verify: 3(5) + 5 = 15 + 5 = 25 ≠ 20. Hmm, conflicting result..."
2. Participant (Model): "Error: Subtraction mistake. 20 - 5 = 15, but 3x = 15 → x = 5 is correct. Verification step has a calculation error."
3. Participant (Human): "Double-check arithmetic: 3(5) + 5 = 15 + 5 = 20. Your verification step was miscalculated."
4. Thinker: "Correction: Verification confirms x = 5. Final answer: x = 5."

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Get Involved

We're just getting started and would love your input! Here are some ways to contribute:

Ideas

• How can we improve the workflow?
• What other use cases can this system support?
• How can we make it easier for non-technical users to participate?

Technical Contributions

• If you have experience building on Nostr, we’d love to hear your insights and ideas.
• Can such a system effectively sustain both synchronous feedback loops (µs to seconds) and asynchronous feedback loops (minutes to hours)?

Feedback

• What challenges do you foresee?
• How can we make the system more robust or user-friendly?

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Next Steps

1. Set up a repository for code and documentation.
2. Build a prototype with basic Thinker/Participant interactions.
3. Experiment with Nostr relays to optimize performance.

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Join the Discussion

Let’s brainstorm and build this together! Share your ideas, questions, or contributions in the comments or by opening a pull request.

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Let’s create a decentralized future for collaborative reasoning!

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Why "Participant" Instead of "Critic"?

• Participants can play multiple roles: critiquing, refining, or adding new insights.
• This terminology is more inclusive and reflects the collaborative nature of the system.

Why Open Collaboration?

• Different models or humans may have access to private or specialized data, making their contributions invaluable.
• By allowing anyone to join, we create a system where the best expertise—whether from a human or a model—can shine.