加密人工智能融合：通过共生解锁技术革命

随着加密货币市场拥抱人工智能 (AI)，与人工智能相关的加密货币有望在 2023 年引领潮流。三个关键领域脱颖而出：众包计算能力、人工智能代理和物联网，以及数据所有权和权利。通过利用区块链技术，这些加密货币为人工智能行业面临的挑战（从芯片短缺到数据来源和主权）提供了解决方案。

The Symbiotic Fusion of Crypto and AI: Harnessing Innovation for a Technological Revolution

Introduction

加密货币与人工智能的共生融合：利用创新推动技术革命简介

The crypto industry has seized upon the burgeoning interest in artificial intelligence (AI), recognizing its transformative potential. AI-adjacent cryptocurrencies have emerged as a dominant narrative, attracting investors and industry enthusiasts alike. This exploration into the convergence of crypto and AI reveals the profound implications and promising opportunities that lie ahead.

加密货币行业抓住了人们对人工智能 (AI) 日益增长的兴趣，认识到了其变革潜力。与人工智能相关的加密货币已成为主流，吸引了投资者和行业爱好者。对加密货币和人工智能融合的探索揭示了未来的深远影响和充满希望的机遇。

Addressing the Chip Shortage through Crowdsourced Computing

通过众包计算解决芯片短缺问题

One compelling use case for blockchain-based systems in AI is crowdsourced computing. This peer-to-peer model connects computing power (GPUs, CPUs, and storage) with engineers requiring machine-learning model training.

人工智能中基于区块链的系统的一个引人注目的用例是众包计算。这种点对点模型将计算能力（GPU、CPU 和存储）与需要机器学习模型训练的工程师连接起来。

The growing lead times for chip orders have raised concerns about a potential chip shortage in 2024. Crowdsourced computing models, such as those offered by the Golem Network (GNT) and Render (RNDR), present a viable solution. These platforms provide a distributed network of computing power that can be rented via their marketplaces, utilizing a blockchain to track usage, invoicing, and payments.

芯片订单交货时间的延长引发了人们对 2024 年可能出现芯片短缺的担忧。众包计算模型，例如 Golem Network (GNT) 和 Render (RNDR) 提供的模型，提供了一种可行的解决方案。这些平台提供了一个分布式计算能力网络，可以通过其市场租赁，利用区块链来跟踪使用情况、发票和付款。

AI Agents and the Internet of Things: Unlocking Digital Autonomy and Seamless Transactions

人工智能代理和物联网：解锁数字自治和无缝交易

AI agents, natural-language-based programs that users interact with, offer significant promise in automating everyday tasks. However, their effectiveness hinges on access to reliable digital payments and infrastructure. Cryptocurrencies serve as an ideal fit, providing secure payment rails for AI agents.

人工智能代理是与用户交互的基于自然语言的程序，为自动化日常任务提供了重要的希望。然而，它们的有效性取决于能否获得可靠的数字支付和基础设施。加密货币是一个理想的选择，为人工智能代理提供安全的支付渠道。

AI agents can also be hosted on a blockchain as smart contracts, enabling seamless integration within the payments system and offering censorship resistance. On-chain agents are gaining traction among traders, who utilize AI trading bots for automated trading and airdrop farming.

人工智能代理还可以作为智能合约托管在区块链上，从而实现支付系统内的无缝集成并提供审查阻力。链上代理在交易者中越来越受欢迎，他们利用人工智能交易机器人进行自动交易和空投农业。

The Internet of Things (IoT), an interconnected network of smart devices, presents another compelling application for AI and crypto. IoT devices may require autonomous transactions, necessitating secure infrastructure and payment mechanisms. Blockchain-based solutions and cryptocurrencies, such as IOTA (IOTA) and Fetch.ai (FET), address this need, enabling secure transactions within the IoT ecosystem.

物联网 (IoT) 是一个智能设备互连网络，为人工智能和加密货币提供了另一个引人注目的应用。物联网设备可能需要自主交易，从而需要安全的基础设施和支付机制。基于区块链的解决方案和加密货币，例如 IOTA (IOTA) 和 Fetch.ai (FET)，可以满足这一需求，从而在物联网生态系统中实现安全交易。

Empowering Data Ownership and Rights

赋予数据所有权和权利

Concerns have risen regarding the training data used by large language models (LLMs), with allegations of copyright violations. Blockchains provide a solution by tracking data provenance, establishing clear ownership records, and facilitating automated royalty payments.

人们对大型语言模型 (LLM) 使用的训练数据的担忧日益增加，并被指控侵犯版权。区块链通过跟踪数据来源、建立清晰的所有权记录并促进自动版税支付提供了解决方案。

Decentralized social networks (DeSoc), such as Farcaster, allow users to monetize their data by opting in to sell it to specific LLMs or marketplaces. This approach offers a competitive edge over traditional platforms that commodify user data without compensation.

Farcaster 等去中心化社交网络 (DeSoc) 允许用户选择将其数据出售给特定的法学硕士或市场，从而将其数据货币化。与将用户数据商品化而无需补偿的传统平台相比，这种方法具有竞争优势。

The Speculative Allure of Crypto-AI Narratives

加密人工智能叙事的投机吸引力

Cryptocurrency markets are often driven by speculation, with narratives influencing price movements even in the absence of tangible fundamentals or use cases. The proximity to trending industries like AI can suffice to propel cryptocurrencies into prominence.

加密货币市场通常是由投机驱动的，即使在缺乏切实的基本面或用例的情况下，叙事也会影响价格走势。与人工智能等热门行业的接近足以推动加密货币脱颖而出。

During the run-up to NVIDIA's GTC conference, AI-adjacent cryptocurrencies experienced significant growth, demonstrating the power of narrative-driven speculation. The crypto-AI narrative is poised for continued success, regardless of the actual relevance of decentralized technologies within the broader AI industry.

在 NVIDIA GTC 会议筹备期间，与人工智能相关的加密货币经历了显着增长，展示了叙事驱动投机的力量。无论去中心化技术在更广泛的人工智能行业中的实际相关性如何，加密人工智能的叙述都将持续成功。

Conclusion

结论

The convergence of crypto and AI presents a multitude of innovative applications, from addressing chip shortages to empowering AI agents and the IoT. The potential for blockchain-based solutions to enhance data ownership and rights is particularly noteworthy. However, the speculative nature of crypto markets should be recognized and underscores the need for a balanced approach that considers both the transformative potential and the risks associated with this emerging field.

加密货币和人工智能的融合带来了多种创新应用，从解决芯片短缺到增强人工智能代理和物联网的能力。基于区块链的解决方案在增强数据所有权和权利方面的潜力尤其值得注意。然而，应该认识到加密市场的投机性质，并强调需要采取平衡的方法，既考虑与这一新兴领域相关的变革潜力和风险。