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umermjd11 edited this page Oct 5, 2026 · 4 revisions

Overview

🚧 This wiki describes DevNet 2.0, soon to be launched. It follows the contracts and dincli on the develop branch; the currently running DevNet may still use older contracts and commands. Pre-launch discussion: #102.

The internet gave everyone a voice. Open-source gave everyone a tool. AI is still waiting.

InfiniteZero is building the commons that changes that.

What is DIN?

DIN (Decentralised Intelligence Network) is the protocol behind the InfiniteZero Network — open infrastructure for a global AI commons, the way the internet itself is a public good.

DIN coordinates federated learning at network scale: millions of devices can contribute quietly to shared AI models, while raw training data never leaves the contributor's device. Only model artifacts — anonymised, encrypted patterns — join the network. Coordination, incentives, and accountability are enforced by smart contracts on Ethereum (the live DevNet runs on Optimism Sepolia), and model artifacts are distributed via IPFS.

Built on Ethereum. Governed by the community. Models belong to the commons.

The DevNet is real infrastructure, not a simulation, and it needs builders. DevNet 2.0 is soon to be launched: it brings the full cryptoeconomic layer (staking, slashing, on-chain rewards and fees) described on these pages.

Why does it exist?

Most AI infrastructure is being built behind closed doors, by a handful of companies, for profit. DIN is the alternative: a live, open, trustless network where the models trained belong to everyone who helped build them. It is designed for anyone who cares about privacy-preserving ML, decentralised systems, or open AI infrastructure.

How it works — in one pass

  1. A model owner registers a model with the protocol, publishing a manifest that describes the model architecture, training logic, and parameters (pinned to IPFS).
  2. Clients train locally. Each client trains the current global model on their own private data — optionally with differential privacy — and submits only the resulting model update.
  3. Auditors evaluate the submitted local models and score them, keeping low-quality or malicious contributions out of the global model.
  4. Aggregators combine the accepted local models into a new global model through two-tier aggregation.
  5. Stakes keep everyone honest. Validators (auditors and aggregators) stake DIN tokens as collateral; misbehaviour is slashed on-chain.
  6. Rewards pay for the work. Each GI has a DIN reward pool, funded before the GI starts. When the GI ends it is split between clients (60%), auditors (20%), aggregators (15%) and the treasury (5%), and participants claim their share on-chain.

This cycle repeats in rounds called Global Iterations (GI), each producing an improved global model.

The building blocks

Component What it does
Platform contracts Seven upgradeable contracts deployed once by the DIN-Representative: DinCoordinator (ETH → DIN purchases, minting gateway, slasher registry), DinToken (ERC-20 utility token), DinValidatorStake (validator staking, slashing, jailing), DINModelRegistry (model admission, open-source or proprietary), DinFeeRouter (fee splitting), DinTreasury (protocol treasury) and DinEmission (per-GI reward subsidy)
Task contracts Deployed per model by its owner: DINTaskCoordinator and DINTaskAuditor run the training lifecycle for that model
dincli Python CLI through which every role — model owner, client, auditor, aggregator, DIN-Representative — interacts with the network
IPFS layer Stores and distributes all off-chain artifacts: model weights, service code, manifests, ABIs

Network roles

  • DIN-Representative — operates the platform-level contracts, admits models, and authorizes task contracts as slashers. On-chain DAO governance is deferred to post-mainnet.
  • Model owners — deploy task contracts, register models (open-source or proprietary), and drive each Global Iteration.
  • Clients — train models locally on private data and submit local model updates.
  • Auditors — stake DIN, evaluate and score submitted local models (commit, then reveal).
  • Aggregators — stake DIN, combine accepted local models into the new global model (commit, then reveal).

Learn more

InfiniteZero Foundation — open AI infrastructure, built by everyone, for everyone.

Introduction

DIN Components

Network Roles

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