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GENESIS Protocol: Building Safe, Transparent AGI

Science & technologyTechnical AI safetyAI governance
🦋

Robert looman

ProposalGrant
Closes August 5th, 2025
$0raised
$250,000minimum funding
$500,000funding goal

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Project Summary


What are this project's goals? How will you achieve them?

I’m building GENESIS — a new AGI architecture that’s lightweight, transparent, and runs on everyday hardware instead of billion-dollar GPU clusters. My goal is to create an AI system whose reasoning is fully visible and traceable, so we can understand how it thinks, align it safely, and make advanced AI accessible to individuals and small teams, not just tech giants.

Instead of relying on giant black-box neural nets, GENESIS uses symbolic memory structures and deterministic reasoning paths. Every step of its thinking can be inspected like code, making it fundamentally safer and more controllable than current LLMs.

I’ve already built working prototypes proving the concept. I’m hitting:

  • Training speeds over 400,000 tokens/sec

  • Custom RAG pipelines handling 1.3 million tokens/sec

  • Symbolic inference speeds exceeding 2 million tokens/sec

My next steps are:

  • Refining the architecture

  • Building user-facing demos

  • Publishing technical documentation

  • Running external audits to prove safety and reproducibility

If we succeed, GENESIS won’t just compete with LLMs — it will redefine what’s possible in safe, democratized AI.


How will this funding be used?

I’m seeking $250,000 to $350,000 to:

  • Fund 12–18 months of full-time development

  • Acquire hardware for testing and scaling prototypes

  • Build an open-source prototype with transparent reasoning chains

  • Develop live demos to show GENESIS answering complex questions with traceable logic paths

  • Hire occasional contractors for UI, optimization, or documentation work

  • Run external audits for safety and reproducibility

  • Cover legal, business, and miscellaneous costs

My vision is to release GENESIS as a public resource so independent developers and researchers can build safe, powerful AI systems without needing massive infrastructure.


Who is on your team? What's your track record on similar projects?

Right now, it’s mostly me. I’m a technical polymath with over 20 years of experience in software engineering, algorithms, systems architecture, and signal processing.

I’ve shipped large-scale software systems, built custom algorithms in domains like audio processing and AI, and run independent R&D projects from scratch.

Over the past year, I’ve funded GENESIS out of pocket — writing prototypes, testing symbolic architectures, and achieving speeds competitive with mainstream AI systems. I’m obsessed with building things that actually work, and with understanding how they work under the hood.

If funding comes through, I plan to add a small team to accelerate development and testing.


What are the most likely causes and outcomes if this project fails?

This is high-risk R&D. The biggest risk is that GENESIS may prove too complex or too resource-intensive to scale up to a practical, general-purpose AGI engine.

Even if it falls short of fully replacing modern LLMs, I believe the project will still produce valuable outputs:

  • New tools for symbolic reasoning

  • Faster and more efficient retrieval systems

  • Safer architectural ideas for building explainable AI

Worst-case, we’d have learned a great deal about how to combine symbolic reasoning with modern AI techniques, and I’d publish those results so others can build on the work.


How much money have you raised in the last 12 months, and from where?

I haven’t raised external funding yet. Everything so far has been bootstrapped from my personal savings.

I’m actively applying to several grants (Emergent Ventures, Nonlinear, others) and exploring potential funding partnerships. Responses are in progress but no funds have landed yet.


Thanks for considering supporting GENESIS. I’m passionate about building AGI that’s safe, transparent, and truly for everyone. Happy to answer any technical questions or share demos.


links:
https://drive.google.com/file/d/1FXHu8r40X7yvNrCeycbz1PipmVvOHoSI/view?usp=drive_link

running code:
https://drive.google.com/file/d/1IzOjA_g7LXYeefASUEelu6u9Ky7YaNus/view?usp=drive_link





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