Trustless Machine Learning Contracts; Evaluating and Exchanging Machine Learning Models on the Ethereum Blockchain

Abstract

Using blockchain technology, it is possible to create contracts that offer a reward in exchange for a trained machine learning model for a particular data set. This would allow users to train machine learning models for a reward in a trustless manner. The smart contract will use the blockchain to automatically validate the solution, so there would be no debate about whether the solution was correct or not. Users who submit the solutions won't have counterparty risk that they won't get paid for their work. Contracts can be created easily by anyone with a dataset, even programmatically by software agents. This creates a market where parties who are good at solving machine learning problems can directly monetize their skillset, and where any organization or software agent that has a problem to solve with AI can solicit solutions from all over the world. This will incentivize the creation of better machine learning models, and make AI more accessible to companies and software agents.

References in corpus (3)

• Achieving Human Parity in Conversational Speech Recognition
• PlaNet - Photo Geolocation with Convolutional Neural Networks
• Under-Optimized Smart Contracts Devour Your Money

Cited by in corpus (7)

• A Secure Federated Learning Framework for 5G Networks
• BlockFLow: An Accountable and Privacy-Preserving Solution for Federated Learning
• A Review on Building Blocks of Decentralized Artificial Intelligence
• Trustable and Automated Machine Learning Running with Blockchain and Its Applications
• Machine Learning on Cloud with Blockchain: A Secure, Verifiable and Fair Approach to Outsource the Linear Regression for Data Analysis
• Agatha: Smart Contract for DNN Computation
• Proof-of-Useful-Work as Dual-Purpose Mechanism for Blockchain and AI: Blockchain Consensus that Enables Privacy Preserving Data Mining