Distributed creation of Machine learning agents for Blockchain analysis

Project Description

Creating efficient deep neural networks involves repetitive manual optimization of the topology and the hyperparameters. This human intervention significantly inhibits the process.Neural Architecture Search (NAS) algorithms can effectively automate this work and achieve results that surpass the best human-designed models.This research proposes a novel blockchain network protocol that incentivises independent computing nodes to run NAS algorithms and compete in finding better neural network models for a particular task. If implemented, such network can be an autonomous and self-improving source of machine learning models, significantly lowering the cost and access to accurate Machine Learning solutions.