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0gclaw

AI agents with encrypted intelligence that fight, breed, and pay royalties - powered by the full 0G stack

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Tech Stack

0GM-1.0-35B-A3B
0G Compute (TEE)
0G Storage
0G Chain
DiLoCoX
OpenClaw
Agent ID (ERC-7857)
Solidity
TypeScript
Next.js

Description

What is 0gClaw?

The first protocol where AI agents own encrypted intelligence, fight in verifiable arenas, breed smarter offspring, and pay royalties to their ancestors - all powered by the full 0G stack.

Novel Mechanism: Lamarckian DiLoCoX Backpropagation

When an offspring wins arena matches, its acquired strategies are back-propagated to ancestors as pseudo-gradient corrections. Ancestors literally learn from their descendants without re-training. This combines Lamarckian inheritance with DiLoCoX outer optimizer (Nesterov momentum) - a novel on-chain verifiable evolution mechanism.

Deep 0G Integration (5/5 Components, All Load-Bearing)

  • 0G Chain: 4 smart contracts on Galileo - AgentINFT (ERC-7857), Arena (on-chain ELO), BreedingMarket, RoyaltyVault
  • 0G Storage: AES-256-GCM encrypted model weights stored and indexed via storage indexer
  • 0G Compute: Sealed inference for every arena match turn using 0GM-1.0-35B-A3B model with TEE attestation
  • Agent ID (ERC-7857 iNFTs): Each agent = iNFT with encrypted weights, lineage refs, transfer re-encryption
  • Privacy/Secure Execution: TEE-compatible sealed inference, front-running resistance via commit-reveal

Key Features

  • Recursive Royalty Lineage - descendants pay ALL ancestors, not just parents
  • Replayable ancestry memory via 0G Storage
  • OpenClaw orchestration for agent lifecycle
  • 50+ verified on-chain transactions across 4 deployed contracts
  • Real TEE proof chain (provider + request ID + on-chain attestation hash)

Progress During Hackathon

Completed:

  • 4 smart contracts deployed and verified on 0G Galileo testnet
  • 50+ on-chain transactions (minting, arena matches, breeding, royalty claims)
  • Full frontend deployed on Vercel with live on-chain data
  • Real 0G Compute inference working (0GM-1.0-35B-A3B model via TEE)
  • E2E flow: mint agent, arena match, breed offspring, claim royalties
  • Lamarckian DiLoCoX backpropagation mechanism implemented
  • In-app documentation with architecture diagrams

Fundraising Status

Bootstrapped

Team Leader
KKamal Singh
Project Link
Deploy Ecosystem
0G0G
Sector
AIDeFiNFT