Decentralized & Collaborative AI on Blockchain

Microsoft Research blog

Overview

Basic explanation: https://aka.ms/0xDeCA10B-blog1

Details and code: https://github.com/Microsoft/0xDeCA10B

Decentralized & Collaborative AI on Blockchain is a framework to host and train publicly available machine learning models while crowdsourcing a dataset. Ideally, using a model’s prediction function is free. An incentive mechanism validates added data as described below.

Picture of a someone sending data to the addData method in CollaborativeTrainer which sends data to the 3 main components as further described next.

  1. The IncentiveMechanism validates the transaction, for instance, in some cases a “stake” or deposit is required.
  2. The DataHandler stores data and meta-data on the blockchain. This ensures that it is accessible for all future uses, not limited to this smart contract.
  3. The machine learning model is updated according to predefined training algorithms. In addition to adding data, anyone can query the model for predictions, and the incentive mechanism may be triggered to provide users with payments or virtual “karma” points.

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