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Project PAI发布 Proof of Useful Work (PoUW) 学术论文

Project PAI发布 Proof of Useful Work (PoUW) 学术论文

有效工作量证明(Proof of Useful Work, PoUW)是一种用来提升区块链效率与安全性的新型共识协议。经典比特币式挖矿的过程十分耗能,因为它所用的工作量证明(Proof of Work, PoW)形如一个抽签机制,底层的计算工作并没有其他用途。矿工们不得不浪费大量能源来添加一个包含交易的新区块到区块链上。作为对比,有效工作量证明除了抽签机制之外还有在区块链上训练一个机器学习模型的功能。

用户可以以不同的身份参与到工作量证明的系统中:客户向网络提交机器学习训练任务;矿工在诚实地进行一定量的机器学习训练工作之后可以得到一次铸造新虚拟货币的机会;协调员协调并监管训练工作的进行。他们的活动不仅保证了区块链的运行,也帮助解决了真实存在的问题:训练机器学习模型。同时客户的隐私也得到了保护,因为他的机器学习任务由分布式网络计算,而不是由一个中心化的机构管理。我们致力于利用区块链的安全性创建更好的人工智能系统。

在本文中,我们简单比较了其他有效工作量证明方案并且列出了本方案的诸多特征。在我们的系统中,用于区块链挖矿计算的nonce变量是通过机器学习训练的输入和中间变量计算而来的。我们实现了一个概念验证级产品,证明了对于客户来说,我们的方案比普通机器学习云计算方案更节省,对于比特币矿工来说,我们的方案收益更高。我们的方案同时也证明了在个人消费级硬件上合作训练机器学习模型可以达到不错的效果。

中文论文下载链接:

https://projectpai.com/assets/files/pouw/PAI_PoUW_Whitepaper_Chinese.pdf

英文论文下载链接:

https://projectpai.com/assets/files/pouw/PAI_PoUW_Whitepaper_English.pdf

Proof of Useful Work (PoUW) is a novel blockchain consensus protocol used to improve efficiency and security of blockchain. Classical Bitcoin mining is a wasteful and resource-intensive process as its Proof of Work (PoW) protocol resembles a lottery and the underlying computational work is not useful otherwise. To add a block of transactions to the blockchain, miners spend a considerable amount of energy. By comparison, PoUW is based on training a machine learning model on the blockchain and does not rely only on the lottery procedure.

Users can participate in PoUW as different roles: clients submit machine learning training tasks to the network; miners get a chance to create new coins after performing honest units of machine learning training work; coordinators manage and supervise the training work. Their activities not only support the blockchain but also contribute to solving real-world problems: training machine learning models. Meanwhile client’s privacy is preserved as machine learning tasks are computed in a distributed manner instead of being managed by a single party. We aim to build better AI systems using the security of the blockchain.

In this paper, we briefly reviewed related PoUW proposals and outlined the unique characteristics of our solution. We proposed a system where nonces for blockchain mining are obtained with a formula that takes into consideration inputs and by-products of the machine learning training. We implemented a proof of concept and showed that our solution is more cost-friendly to a client than regular cloud ML training, but also more profitable to miners compared to Bitcoin mining. Our approach also shows that ML models can be trained collectively with good performance using commodity hardware owned by individuals.

Here’s a link to the paper:

https://projectpai.com/assets/files/pouw/PAI_PoUW_Whitepaper_English.pdf

官网订阅并收取 Project PAI 最新报道

https://projectpai.com/zh/chn-home/#sign

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