AI News 02月28日
Trust meets efficiency: AI and blockchain mutuality
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人工智能(AI)与区块链技术之间并非简单的融合,而是一种互利共生的关系。区块链为AI提供了透明、去中心化的基础设施,解决了AI模型在数据完整性和偏差方面面临的挑战,增强了AI的可信度。同时,AI通过其强大的数据分析能力和自动化能力,提升了区块链网络的效率和安全性,例如实时监控区块链活动以识别异常,优化DeFi协议中的收益策略等。两者结合,在供应链管理、能源优化等领域展现出巨大的应用潜力,共同推动数字技术向更智能、更可靠的方向发展。

🤝区块链技术为人工智能提供了一个去中心化的基础设施,从而促进信任和协作。诸如Ocean Protocol之类的平台使用区块链来记录AI训练数据,在不损害所有权的情况下提供可追溯性。

🛡️人工智能可以通过管理零知识证明和其他加密技术来保护用户数据,从而提高隐私性。AI还可以实时监控区块链活动,以比手动扫描更快地识别异常情况,从而加强安全性。

💡人工智能和区块链的结合已经在现实世界中产生了影响。在供应链中,人工智能有助于优化物流,而区块链可以追踪物品的来源。在能源领域,基于区块链的智能电网与人工智能相结合可以预测需求。

Blockchain has tried to claim many things as its own over the years, from global payment processing to real-world assets. But in artificial intelligence, it’s found synergy with a sector willing to give something back. As this symbiotic relationship has grown, it’s become routine to hear AI and blockchain mentioned in the same breath.

While the benefits web3 technology can bring to artificial intelligence are well documented – transparency, P2P economies, tokenisation, censorship resistance, and so on – this is a reciprocal arrangement. In return, AI is fortifying blockchain projects in different ways, enhancing the ability to process vast datasets, and automating on-chain processes. The relationship may have taken a while to get started, but blockchain and AI are now entwined.

Trust meets efficiency

While AI brings intelligent automation and data-driven decision-making, blockchain offers security, decentralisation, and transparency. Together, they can address each other’s limitations, offering new opportunities in digital and real-world industries. Blockchain provides a tamper-proof foundation and AI brings adaptability, plus the ability to optimise complex systems.

Together, the two promise to enhance scalability, security, and privacy – key pillars for modern finance and supply chain applications.

AI’s ability to analyse large amounts of data is a natural fit for blockchain networks, allowing data archives to be processed in real time. Machine learning algorithms can predict network congestion – as seen with tools like Chainlink’s off-chain computation, which offers dynamic fee adjustments or transaction prioritisation.

Security also gains: AI can monitor blockchain activity in real-time to identify anomalies more quickly than manual scans, so teams can move to mitigate attacks. Privacy is improved, with AI managing zero-knowledge proofs and other cryptographic techniques to shield user data; methods explored by projects like Zcash. These types of enhancements make blockchain more robust and attractive to the enterprise.

In DeFi, Giza‘s agent-driven markets embody the convergence of web3 and artificial intelligence. Its protocol runs autonomous agents like ARMA, which manage yield strategies across protocols and offer real-time adaptation. Secured by smart accounts and decentralised execution, agents can deliver positive yields, and currently manage hundreds of thousands of dollars in on-chain assets. Giza shows how AI can optimise decentralised finance and is a project that uses the two technologies to good effect.

Blockchain as AI’s backbone

Blockchain offers AI a decentralised infrastructure to foster trust and collaboration. AI models, often opaque and centralised, face scrutiny over data integrity and bias – issues blockchain counters with transparent, immutable records. Platforms like Ocean Protocol use blockchain to log AI training data, providing traceability without compromising ownership. That can be a boon for sectors like healthcare, where the need for verifiable analytics is important.

Decentralisation also enables secure multi-party computation, where AI agents collaborate across organisations – think federated learning for drug discovery – without a central authority, as demonstrated in 2024 by IBM’s blockchain AI pilots. The trustless framework reduces reliance on big tech, helping to democratise AI.

While AI can enhance blockchain performance, blockchain itself can provide a foundation for ethical and secure AI deployment. The transparency and immutability with which blockchain is associated can mitigate AI-related risks by ensuring AI model integrity, for example. AI algorithms and training datasets can be recorded on-chain so they’re auditable. Web3 technology helps in governance models for AI, as stakeholders can oversee and regulate project development, reducing the risks of biased or unethical AI.

Digital technologies with real-world impact

The synergy between blockchain and AI exists now. In supply chains, AI helps to optimise logistics while blockchain can track item provenance. In energy, blockchain-based smart grids paired with AI can predict demand; Siemens reported a 15% efficiency gain in a 2024 trial of such a system in Germany. These cases highlight how AI scales blockchain’s utility, while the latter’s security can realise AI’s potential. Together, they create smart, reliable systems.

The relationship between AI and blockchain is less a merger than a mutual enhancement. Blockchain’s trust and decentralisation ground AI’s adaptability, while AI’s optimisation unlocks blockchain’s potential beyond that of a static ledger. From supply chain transparency to DeFi’s capital efficiency, their combined impact is tangible, yet their relationship is just beginning.

(Image source: Unsplash)

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区块链 人工智能 DeFi 数据安全
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