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A Proof of Useful Work for Artificial Intelligence on the Blockchain
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Bitcoin mining is a wasteful and resource-intensive process. To add a block of transactions to the blockchain, miners spend a considerable amount of energy. The Bitcoin protocol, named 'proof of work' (PoW), resembles a lottery and the underlying computational work is not useful otherwise. In this paper, we describe a novel 'proof of useful work' (PoUW) protocol based on training a machine learning model on the blockchain. Miners get a chance to create new coins after performing honest ML training work. Clients submit tasks and pay all training contributors. This is an extra incentive to participate in the network because the system does not rely only on the lottery procedure. Using our consensus protocol, interested parties can order, complete, and verify useful work in a distributed environment. We outline mechanisms to reward useful work and punish malicious actors. We aim to build better AI systems using the security of the blockchain.
Forward citations
Cited by 2 Pith papers
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Proof of Work With External Utilities
In a Proof-of-Useful-Work model with quadratic costs and linear block rewards, the unique equilibrium has every miner participating, and miners profit most by concentrating their useful tasks into one block.
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SEDULity: A Proof-of-Learning Framework for Distributed and Secure Blockchains with Efficient Useful Work
A proof-of-learning blockchain in which each miner trains a separate ML task and a block is a hash of the resulting model checkpoint is proposed.
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