区块链领导者 nChain 表示其技术可以在确保人工智能模型安全可靠方面发挥重要作用

9 月份，该公司成功演示了一种以加密方式证明人工智能模型是在特定数据集上进行训练的方法，并且没有任何内容被篡改。

Blockchain technology company nChain has highlighted the potential role its technology could play in ensuring the security and trustworthiness of artificial intelligence (AI) models. In September, nChain demonstrated a method to cryptographically prove an AI model's training on a specific dataset without any tampering. This was achieved through on-chain transactions on the BSV mainnet, utilizing Zero-Knowledge Proof (ZKP) techniques to verify the existence of information without revealing it publicly.

区块链技术公司 nChain 强调了其技术在确保人工智能 (AI) 模型的安全性和可信度方面可以发挥的潜在作用。 9 月，nChain 演示了一种以加密方式证明 AI 模型在特定数据集上进行训练而无需任何篡改的方法。这是通过 BSV 主网上的链上交易实现的，利用零知识证明（ZKP）技术来验证信息的存在而无需公开披露。

The ability to record and verify proprietary information is crucial for AI developers, who must maintain confidentiality for competitive purposes while also assuring regulators and the public that their systems are developed responsibly. nChain has recorded the relevant transaction and made the tools used available on its GitHub page.

记录和验证专有信息的能力对于人工智能开发人员来说至关重要，他们必须出于竞争目的保密，同时还要向监管机构和公众保证他们的系统是负责任地开发的。 nChain 已记录相关交易，并在其 GitHub 页面上提供了所使用的工具。

This serves as another example of BSV's capability to enter new industry segments and even create entirely new industries by leveraging its key features of speed, unbounded scalability, and affordability. Data is secured by the proven proof-of-work (PoW) transaction verification algorithm rather than the less secure proof-of-stake (PoS) algorithm. The BSV network can perform tasks that other UTXO-based PoW blockchain networks simply cannot handle.

这是 BSV 有能力利用其速度、无限可扩展性和可承受性等关键特性进入新行业领域甚至创建全新行业的另一个例子。数据通过经过验证的工作量证明 (PoW) 交易验证算法而不是安全性较低的权益证明 (PoS) 算法来保护。 BSV 网络可以执行其他基于 UTXO 的 PoW 区块链网络根本无法处理的任务。

Verifiable AI is a relatively new industry sector with promising potential. At present, the field is primarily the domain of academics and researchers, with little in the way of commercial activity. When it comes to training data, weights and algorithms, the well-known AI firms are jealously guarding their secrets, presenting only a “black box” as the final product they expect end users to trust, as long as it works.

可验证的人工智能是一个相对较新的行业领域，潜力巨大。目前，该领域主要是学者和研究人员的领域，商业活动很少。当谈到训练数据、权重和算法时，著名的人工智能公司都小心翼翼地保守着自己的秘密，只提供一个“黑匣子”作为他们希望最终用户信任的最终产品，只要它有效。

So a problem arises that could impact the industry in several ways: companies are in a fiercely contested race to build the most advanced AI, and the prize for winning that contest (or even stages of it) could bring them immense wealth and power. At the same ime, governments and the public are wary of the secretive way AI is being developed, which builds mistrust in AI technology overall. Developers need to balance these two driving forces to achieve their goals (and possibly avoid the imposition of crippling regulations).

因此，出现了一个问题，可能会在多个方面影响该行业：公司正在进行一场激烈的竞赛，以构建最先进的人工智能，而赢得这场竞赛（甚至是阶段性竞赛）的奖项可能会给他们带来巨大的财富和权力。与此同时，政府和公众对人工智能开发的秘密方式持谨慎态度，这对人工智能技术产生了整体不信任。开发人员需要平衡这两种驱动力以实现其目标（并可能避免实施严厉的法规）。

According to nChain Research Director Dr. Wei Zhang, this is where blockchain and ZKPs could provide the perfect solution. He wrote in a blog post that major AI players must “demonstrate that an AI system operates according to its specifications, free of critical bugs and adheres to ethical standards such as fairness, transparency and safety, ideally without revealing proprietary information of the system.”

nChain 研究总监张伟博士表示，这就是区块链和 ZKP 可以提供完美解决方案的地方。他在一篇博客文章中写道，主要人工智能参与者必须“证明人工智能系统按照其规范运行，不存在严重错误，并遵守公平、透明和安全等道德标准，最好不泄露系统的专有信息。”

ZKPs are a way of proving that information exists and that you possess it without revealing its contents. Hypothetical but simpler blockchain applications of ZKPs include an identity document that could prove you're a certain age or reside in a certain place without needing to show those precise details to anybody. Another could prove you have adequate net worth to invest in a project without explicitly stating how much money you have.

ZKP 是一种证明信息存在并且您拥有它而不泄露其内容的方法。假设但更简单的 ZKP 区块链应用程序包括一个身份证件，可以证明您达到一定年龄或居住在某个地方，而无需向任何人显示这些精确的详细信息。另一种方法可以证明您有足够的净资产来投资某个项目，而无需明确说明您有多少钱。

Similarly, companies involved in AI development could use blockchain records to verify their machine learning weights and models, that training data and safety standards are sound, and that their AI model is following the guidelines they claim it to be without the risk of that information leaking to competitors.

同样，参与人工智能开发的公司可以使用区块链记录来验证他们的机器学习权重和模型，训练数据和安全标准是否健全，以及他们的人工智能模型遵循他们声称的指导方针，而不存在信息泄露的风险给竞争对手。

While the ZKP concept has been around since the 1980s, the computation required to process the necessary cryptographic methods known as zk-SNARKS (that's Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge) or STARKS (Scalable Transparent Arguments of Knowledge) makes it a difficult task for most blockchain networks.

虽然 ZKP 概念自 20 世纪 80 年代以来就已存在，但处理称为 zk-SNARKS（零知识简洁非交互式知识论证）或 STARKS（可扩展透明知识论证）的必要加密方法所需的计算使其成为对于大多数区块链网络来说，这是一项艰巨的任务。

“When you think of ZKPs, there are two parts: proof generation, and proof verification,” Zhang told CoinGeek. “For SNARKS, in this particular context, the schemes we're using are always trying to achieve efficient verification.”

“当你想到 ZKP 时，有两个部分：证明生成和证明验证，”Zhang 告诉 CoinGeek。 “对于 SNARKS 来说，在这个特定的背景下，我们使用的方案总是试图实现高效的验证。”

“Blockchain is very expensive for on-chain computation. If on-chain computation is only restricted to verification, then it works because the heavy duty is on the proof generation side, and that is off-chain.”

“区块链对于链上计算来说非常昂贵。如果链上计算仅限于验证，那么它是有效的，因为繁重的任务是在证明生成方面，而这是链下的。”

Several teams are working on ways to do this besides nChain, on other blockchain networks including Ethereum and BTC. ZKPs are computationally intensive to perform. There are two parts to it: generating the proof; and verifying it. Both ETH and BTC run up against the same scaling limitations that have plagued their networks for years with other applications.

除了 nChain 之外，还有几个团队正在以太坊和 BTC 等其他区块链网络上研究实现这一目标的方法。 ZKP 的执行需要大量计算。它有两个部分：生成证明；并验证它。 ETH 和 BTC 都面临着相同的扩展限制，这些限制多年来一直困扰着它们的网络的其他应用程序。

“They made verification feasible on-chain, great. And everyone is in a race trying to make the proof generation less of a burden. At the moment, you can do that for specific computation, or set of computations, but it's very difficult to have a universal approach such that the proof generation is feasible for any computation.”

“他们使链上验证变得可行，太棒了。每个人都在努力减轻证明生成的负担。目前，您可以针对特定计算或一组计算执行此操作，但很难有一种通用方法使得证明生成对于任何计算都是可行的。”

BTC as it exists today is way too limited in data capacity to perform the task, but there have been moderately successful attempts by BitVM and StarkWare at verifying STARK proofs, using the BTC testnet “Signet” (where OP_CAT has been enabled), and the recently touted “Fractal Bitcoin” (which could be described as a copy of Signet with an exotic mining mechanism). Fractal Bitcoin's feasibility

目前的 BTC 数据容量太有限，无法执行该任务，但 BitVM 和 StarkWare 使用 BTC 测试网“Signet”（已启用 OP_CAT）在验证 STARK 证明方面进行了相当成功的尝试，并且最近吹捧的“分形比特币”（可以被描述为具有奇异挖矿机制的 Signet 副本）。分形比特币的可行性