Trusted, Scalable AGI on Verifiable Open Hardware

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Vinay Devabhakthuni
Project Owner

Trusted, Scalable AGI on Verifiable Open Hardware

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Overview

We propose a novel AGI hardware stack combining RISC-V microarchitectures, symbolic reasoning runtimes and zero-knowledge proof systems (RISC Zero). This enables decentralized, verifiable AGI agents to run on edge devices like phones, drones or sensors. Our stack supports MeTTa logic, outputs cryptographic proofs of decision-making and includes an SDK for SingularityNET integration. Optional neuromorphic hooks enable hybrid reasoning. All components are open-source, scalable and optimized for low-power, trustless deployment.

RFP Guidelines

Explore novel hardware architectures and computing paradigms for AGI

Proposal Submission (5 days left)
  • Type SingularityNET RFP
  • Total RFP Funding $80,000 USD
  • Proposals 5
  • Awarded Projects n/a
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SingularityNET
Apr. 14, 2025

The purpose of this RFP is to identify, assess, and experiment with novel computing paradigms that could enhance AGI system performance and efficiency. By focusing on alternative architectures, this research aims to overcome computational bottlenecks in recursive reasoning, probabilistic inference, attention allocation, and large-scale knowledge representation. Bids are expected to range from $40,000 - $80,000.

Proposal Description

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  • Total Milestones

    4

  • Total Budget

    $80,000 USD

  • Last Updated

    21 May 2025

Milestone 1 - Architecture & Runtime Prototype

Description

Establish the foundational architecture for the AGI hardware stack. Select RISC-V hardware targets (real or emulated) and build a functional prototype of a symbolic reasoning runtime compatible with MeTTa-style logic.

Deliverables

A documented architecture design, working symbolic logic interpreter (basic MeTTa or equivalent) running on QEMU/emulator or low-power RISC-V board and initial logic test cases.

Budget

$20,000 USD

Success Criterion

- Finalized architecture document (hardware + runtime + proof layer plan) - Symbolic interpreter runs on RISC-V (real/emulated) with ≥ 3 test cases - Code published in a versioned repository with initial documentation

Milestone 2 - ZK Proof Engine Integration

Description

Integrate the RISC Zero zkVM into the symbolic runtime layer, enabling cryptographic proof-of-execution for AGI decisions. The focus is on verifying that an agent followed its encoded logic.

Deliverables

A prototype integration between the runtime and RISC Zero zkVM, demonstrating generation of zero-knowledge proofs for logic evaluation paths e.g., A DAG traversal or rule execution.

Budget

$20,000 USD

Success Criterion

- Functional proof-of-execution output from symbolic runtime - Proof size ≤ 150KB; generation time ≤ 5 seconds (for test cases) - Public test suite demonstrating ZKP behavior with example logic

Milestone 3 - Edge SDK + Simulation Testbed

Description

Develop a QEMU/Docker-based simulation environment and an SDK that allows developers to package and deploy symbolic AGI logic to RISC-V edge targets. This includes CLI tools and integration hooks.

Deliverables

A developer SDK and CLI tool to deploy logic modules, a simulation testbed with runtime and proof layer integration and example workflows for deployment and testing.

Budget

$20,000 USD

Success Criterion

- CLI tool enables logic packaging and deployment in simulation - QEMU/Docker testbed runs integrated stack (runtime + zkVM) - Documentation + 1 tutorial covering agent deployment and testing

Milestone 4 - Final Benchmarks, Docs & Public Release

Description

Complete project with performance benchmarks, power profiling (if hardware used) and public release of all components. Include integration demo for SingularityNET-compatible agents and onboarding materials.

Deliverables

Performance report, public GitHub repository with MIT/Apache 2.0 license, final codebase, user docs and demo AGI agent. Optional delivery of a recorded demo or live walkthrough.

Budget

$20,000 USD

Success Criterion

- Benchmark report: symbolic ops/sec, ZKP latency, resource usage - Code, SDK, and docs publicly accessible and reproducible - Demo agent integrated with SingularityNET container/interface

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