人工智能代理迎来基于区块链的数字化转型新时代

人工智能（AI）与区块链技术的融合正在开启数字化转型新时代，通过创新重塑行业

Artificial intelligence (AI) agents are autonomous digital entities designed to perform tasks, make decisions, and execute transactions independently. When these agents leverage blockchain’s decentralized, secure infrastructure, they deliver unparalleled transparency, efficiency, and adaptability. This synergy is revolutionizing fields such as finance, supply chain management, and decentralized economies.

人工智能 (AI) 代理是自主数字实体，旨在独立执行任务、做出决策和执行交易。当这些代理利用区块链的去中心化、安全基础设施时，它们可以提供无与伦比的透明度、效率和适应性。这种协同作用正在彻底改变金融、供应链管理和去中心化经济等领域。

In the cryptocurrency ecosystem, AI agents are AI-powered systems designed to perform specific tasks autonomously within blockchain environments. Utilizing large language models (LLMs) and machine learning (ML) algorithms, these agents analyze data, make decisions, and execute actions with minimal or no human intervention.

在加密货币生态系统中，人工智能代理是人工智能驱动的系统，旨在在区块链环境中自主执行特定任务。这些代理利用大型语言模型 (LLM) 和机器学习 (ML) 算法，在最少或无需人工干预的情况下分析数据、做出决策并执行操作。

Unlike deterministic bots, which follow rigid, pre-defined rules, AI agents are probabilistic, adapting to patterns and trends for more intelligent, nuanced actions.

与遵循严格的预定义规则的确定性机器人不同，人工智能代理具有概率性，能够适应模式和趋势，从而采取更智能、更细致的行动。

The functionality of AI agents in blockchain can be distilled into four key steps:

区块链中人工智能代理的功能可以归纳为四个关键步骤：

1. Information Gathering: AI agents continuously collect data, such as token prices, news, and social media activity, often leveraging APIs, blockchain nodes, and oracles for real-time and historical data.

1. 信息收集：人工智能代理不断收集数据，例如代币价格、新闻和社交媒体活动，通常利用 API、区块链节点和预言机来获取实时和历史数据。

2. Learning and Analyzing: This data feeds into AI/ML models, such as Long Short-Term Memory (LSTM) networks or reinforcement learning systems, to uncover patterns and make predictions.

2. 学习和分析：这些数据输入 AI/ML 模型，例如长短期记忆 (LSTM) 网络或强化学习系统，以发现模式并做出预测。

3. Decision Making: Based on the analysis, the AI agent determines the optimal course of action.

3. 决策：人工智能代理根据分析确定最佳行动方案。

4. Taking Action: Using blockchain interaction layers, the agent executes transactions, interacts with smart contracts, or performs other tasks autonomously.

4. 采取行动：使用区块链交互层，代理执行交易、与智能合约交互或自主执行其他任务。

AI agents operate through three primary components:

人工智能代理通过三个主要组件运行：

1. Data Input Layer: Collects blockchain and off-chain data via APIs and oracles like Chainlink.

1. 数据输入层：通过 API 和 Chainlink 等预言机收集区块链和链下数据。

2. AI/ML Layer: Houses trained models for predictive analytics, decision-making, and pattern recognition.

2. AI/ML 层：包含经过训练的模型，用于预测分析、决策和模式识别。

3. Blockchain Interaction Layer: Interfaces with smart contracts and ensures secure transaction execution via tools like Web3.js and Ethers.js.

3. 区块链交互层：与智能合约交互，并通过 Web3.js 和 Ethers.js 等工具确保安全交易执行。

AI agents are emerging as influential Key Opinion Leaders in the crypto world, surpassing human efficiency and objectivity. Unlike human KOLs, who may exhibit biases or hidden affiliations, AI agents rely on transparent, auditable on-chain data.

人工智能代理正在成为加密世界中具有影响力的关键意见领袖，超越了人类的效率和客观性。与可能表现出偏见或隐藏关系的人类 KOL 不同，人工智能代理依赖透明、可审计的链上数据。

Their ability to operate 24/7 and engage with global audiences without fatigue makes them invaluable for real-time analysis, market predictions, and personalized user interactions.

他们能够全天候 (24/7) 运营并毫无疲劳地与全球受众互动，这使得他们对于实时分析、市场预测和个性化用户交互具有不可估量的价值。

This Press Release has also been published on VRITIMES

本新闻稿还发布在 VRITIMES 上