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Proof of Training protocol aims to make blockchains more energy efficient

By PulseAugur Editorial · [1 sources] ·

Researchers have proposed a new protocol called Proof of Training (PoT) to enable blockchains to reliably train machine learning models. This approach aims to repurpose the significant computational power currently used for energy-intensive hash puzzles in proof-of-work networks towards valuable machine learning tasks. The PoT protocol is designed to maintain the incentive structures of blockchains while ensuring the reliability, security, and scalability of the training process. AI

IMPACT This research could lead to more energy-efficient and decentralized methods for training AI models by leveraging existing blockchain infrastructure.

RANK_REASON This is a research paper introducing a novel protocol for training machine learning models on blockchains. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Proof of Training protocol aims to make blockchains more energy efficient

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This is a research paper introducing a novel protocol for training machine learning models on blockchains. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Peihao Li, Nadia Dahmani ·

    Can Blockchains Reliably Train Machine Learning Models?

    arXiv:2307.07066v2 Announce Type: replace-cross Abstract: Large proof of work (PoW) networks allow anyone to earn rewards by running computation-intensive hash puzzles for profit, yet they typically consume electricity comparable to that of medium-sized countries. Repurposing com…

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