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@hetu-project

Hetu Protocol

Deep Intelligence Society

HETU: Deep Intelligence Society

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Hetu is building a deeply entangled intersubjective reality where humans and intelligence co-create. Our mission is to dissolve the trust gap between humans and intelligence, evolving towards a self-incentivized, self-evolving, self-operating society of deep intelligence.

Mainnet — Foundational Pillars

PillarRoleOutputLayer
Deep Intelligence MarketCapital Formation for IntelligenceMonetization, stablecoin liquidity, agent IPOsEconomic Layer
Truth EngineAttribution & ConsensusCausal graphs, incentives, trustless auditTruth Layer
Hyper-Scalable Layer 2Execution for Scientific-Grade AIReal-time, low-latency compute and coordinationInfra Layer

🧠 1. Deep Intelligence Market

Economic Layer — Redefining capital formation around intelligence as an asset class, backed by measurable contribution and utility.

Key Features:

  • EVM-compatible Mainnet/Subnet architecture.
  • Decentralized Mixture-of-Experts (MoE) + training models.
  • Consensus via Proof-of-Intelligence in expert model routing/aggregation.
  • Dynamic model selection to incentivize new entrants.
  • Intelligence Mining — Rewards based on compute + verifiable contribution.
  • Native support for AI-for-Science workloads.

Economic Components:

  • HETU Mining — Mint tokens based on verifiable AI contribution (Proof of Execution & Contribution).
  • AI-Stablecoin Payment Protocol — Stake HETU to mint stablecoins for licensing, microtransactions, and event-based payments.
  • AI-NativeCoin / AI RBO (Revenue-Based Offering) — Tokenized, programmable cash flow rights for intelligence assets, enabling DeFi-style liquidity and financing.

🧩 2. Truth Engine

Consensus & Attribution Layer — Audits, attributes, and rewards AI based on real utility.

Core Mechanisms:

  • Verifiable AI Utility — Proofs for every inference, interaction, and data contribution.
  • Proof of Causal Work (PoCW) — Directed Acyclic Graph (DAG) of events and their causal relationships; rewards based on causal weight.
  • Intersubjectivity Framework — Bridges human metrics and agent-native consensus.
  • Hyper-Scalability.

⚙️ 3. Hyper-Scalable Layer 2

Execution Layer — Scientific-grade AI computation with high throughput and low latency.

Performance Benchmarks:

  • TPS: 210,000+
  • Finality: 400ms

Architecture:

  • Sequencer Layer — Fast transaction ordering, real-time coordination.
  • DAG-based BFT Layer — High-throughput finality engine optimized for AI/science workloads.

Subnet

VerticalFocusCore Mechanism
🤖 AI MoneyMonetization of intelligence$AI-NativeCoin (CVF, RVF), AI-Stablecoins
🔬 AI for ScienceScientific data assetizationEncrypted data pipelines, model licensing
💸 AIFiIntelligence × Financial marketsAI × RWA, cash flow keys

🤖 AI Money

  • Trades programmable cash flow rights (CVF, RVF).
  • Verifiable cashflow auditing, real-time monetization, native AI yield loops.

🔬 AI for Science (AI4SCI)

  • On-chain scientific provenance, dataset licensing, open AI/Science marketplaces.

💸 AIFi — Deep Intelligence Finance

  • Brings RWA and capital markets on-chain.

👥Hetu Cofounders

Hetu Key Research of VLC:

Hetu Key Consensus Research:

Hetu Key AI Research:

Hetu Website

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