Concept & architecture

The decentralized nature of EtherMind also means that creators retain more control over their work, benefiting from direct sales and potentially greater transparency in transactions.

Below is the technical architecture, key features, marketing strategies, and operational considerations necessary to bring this innovative platform for the grant proposal.

1. Concept

EtherMind - A Decentralized AI Marketplace that facilitates the buying, selling, and trading of AI models and datasets in a secure, transparent, and efficient manner.

Leveraging blockchain technology ensures integrity, provenance, and compensation mechanisms for contributors.

2. Technical Architecture

# Blockchain

• Choice of Blockchain: Ethereum for its mature ecosystem and smart contract capabilities, and Solana for low fees and scalability, depending on transaction cost and speed requirements. ( sol, eclipse, base)

• Smart Contracts: To handle transactions, user registration, AI model/dataset listings, and staking mechanisms.

# AI Model Storage and Execution

• Decentralized Storage: IPFS (InterPlanetary File System) for storing AI models and datasets, ensuring availability and integrity.

• Execution Environment: Use secure, decentralized computing platforms like Golem or iExec for model training and execution, ensuring users can run AI models without compromising their own computational resources.

# Frontend and User Interface

• Web Application: A user-friendly interface for browsing, uploading, and purchasing AI models and datasets.

• Technologies - Next JS for the front end, Tailwind CSS for UI Design and Web3.js or Ethers.js for blockchain interactions.

# Identity and Security

• Decentralized Identity: Implement DID (Decentralized Identifiers) for secure and verifiable user identities.

• Security Measures: Regular security audits, encryption of sensitive data, and secure smart contract development practices.

# Privacy

• use of zklogin solutions to be explored.

• options such as - zksync/risczero