ZeroNetAI

🧠 “Imagine if everyone could train and run their own AI agent — on their laptop — using just 1.2 GB.”

No GPUs. No cloud APIs. Just a CPU and a command line.

That’s now possible thanks to two breakthroughs: Microsoft’s BitNet — a CPU-trainable LLM, and ZKML — cryptography that proves an AI did what it claimed to do.

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Introducing ZeronetAI, powered by our protocol: SAP — Sovereign Agents Protocol.

ZeronetAI is a decentralized AI infrastructure where anyone can: 1. 🖥️ Download and run a 1.2 GB BitNet model on a standard laptop 2. 🔐 Create a unique hash of their local agent (based on weights + config) 3. 🧠 Use that agent to perform tasks like summarizing, ranking, or labeling 4. ✅ Generate a ZK proof that their agent performed the task correctly 5. 🌐 Submit the proof onchain to verify and receive a reward

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No servers. No trust. No GPU needed.

You truly own your agent. You run it. You prove what it did — and earn for it.

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We’ve built the MVP: • BitNet model runs on CPU (~1.2 GB, 3B parameters) • Agent hash generation with Poseidon • Task: basic NLP (e.g. text classification) • Proof: ZKML stack (EZKL, Giza, RISC Zero) • Reward flow: testnet integration live

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ZeronetAI brings sovereignty to AI. Just like crypto gave us ownership of money — we now own, run, and prove our AI.

The future is small, local, and cryptographically verifiable.

🛠️ Technology Deep Dive Frontend Foundation React 18 with TypeScript for type safety Vite for lightning-fast development and HMR Tailwind CSS with custom design system for glass morphism effects React Flow for visual workflow designer D3.js for automatic layout algorithms (dagre, hierarchy, tree) Blockchain & Identity Layer Wagmi v2 for Web3 wallet integration RainbowKit for beautiful wallet connection UI WorldID for human verification with cryptographic proofs Hardhat for smart contract deployment Custom bypass system for development mode AI/LLM Integration zkVM BitNet models (B1.58 Large, 1B, 3B parameters) Local LLM support: compatible APIs Streaming responses with real-time typing effects Cryptographic proof verification for AI computations