加密 AI 代理:链上经济的一等公民

foresightnewsPublicado a 2023-12-05Actualizado a 2023-12-13

Resumen

AI 代理正在崛起成为加密经济中不可忽视的力量。

AI 代理正在崛起成为加密经济中不可忽视的力量。


撰文:Mason Nystrom,Variant Fund 投资合伙人

编译:Luffy,Foresight News


机器人正在成为加密经济的一等公民。 


这种趋势是显而易见的。搜索者部署 Jaredfromsubway.eth 这样的机器人,通过抢先交易来利用人类用户对便利的渴望。 Banana Gun 和 Maestro 一直是以太坊上 Gas 消耗大户,它们允许用户启用机器人通过 Telegram 进行便捷交易。现在,在 Friend.tech 等社交应用上,当应用程序获得初步的人类用户采纳后,机器人也会加入进来,并无意中进一步推动投机飞轮。


这一切都表明表明,机器人,无论是利润驱动的(例如 MEV 机器人)还是消费者驱动的(例如 Telegram 机器人),都正在成为区块链上的优先用户。 


虽然到目前为止,加密领域的机器人还相当初级,但由于大型语言模型(LLM)的兴起,加密领域之外的机器人已经开始发展成为强大的人工智能代理,其最终目标是自主处理复杂的任务并让任务决策更加明智。 



在加密领域构建这些人工智能代理带来了几个重要的增强功能: 


原生支付流:人工智能代理可以存在于加密货币之外,但如果我们希望人工智能代理执行复杂的操作,他们将需要获得资金。与让人工智能代理访问银行账户、支付程序(例如 Stripe)或处理链下世界中存在的绝大多数其他低效问题相比,加密货币使人工智能代理能够获得资金,这是一项意义非凡的改进。


AI 代理钱包所有权:连接到钱包的 AI 代理将能够拥有资产(例如 NFT 等),从而赋予 AI 代理所有加密资产固有的数字产权。这对于代理之间的交易尤其重要。


可验证的、确定性的操作:当操作可证明时,人工智能代理将最有效(它们可以确保某些操作已完成)。链上交易本质上是确定性的——要么发生,要么没有——这意味着人工智能代理将能够更准确地完成链上任务。 


当然,链上人工智能代理也有​​局限性。


一个限制是人工智能代理需要执行链下逻辑才能保持高性能。这意味着链上人工智能代理将在链下托管其逻辑 / 计算以优化效率,但代理决策将在链上执行。重要的是,AI 代理还可以使用 Modulus 等 zkML 提供商来确保其链下数据输入得到验证。 


人工智能代理的另一个主要限制是它们的有用性取决于它们所提供的工具。例如,如果你要求代理提供实时新闻事件的摘要,则代理的工具包中需要有一个网络爬虫来梳理互联网信息以执行给定的任务。如果你需要代理将响应保存为 PDF,那么代理工具包中需要有一个文件系统。如果想要代理跟单交易你最喜欢的加密推特 KOL,那么代理需要访问钱包并获得该钱包的私钥签名权限。


纵观当前从确定性到非确定性的情况,大多数加密人工智能代理都执行确定性任务。也就是说,人类对任务的参数以及如何完成任务(例如代币交换)进行编程。 



加密 AI 代理已经从早期的 keeper 机器人(目前仍在 DeFi 和预言机应用程序中使用)发展到今天利用 LLM 的更复杂的代理,比如像 Botto 这样的自主艺术家;人工智能代理可以使用 Syndicate 的交易云为自己提供银行服务;以及早期的人工智能代理服务市场,例如 Autonolas。 


各种令人兴奋的前沿应用已经出现:


支持 AI 代理的「智能钱包」:Dawn 利用 DawnAI 提供 AI 代理,可以帮助用户发送交易、执行交易和其他实时链上洞察。 


加密游戏代理:Parallel Alpha 的最新游戏 Colony 旨在创建可以拥有钱包并相互交易的 AI 角色。 


AI 代理的增强工具包:AI 代理的能力取决于其工具包,与区块链的交互目前是一个新兴领域。加密 AI 代理需要钱包、访问资金、许可功能、集成 AI 模型以及与其他代理交互的能力。更具体地说,Gnosis 通过其 AI mechs 展示了一个早期基础设施, 它用智能合约包装 AI 脚本,以便任何人(包括其他机器人)都可以调用智能合约来执行代理操作(例如,在预测市场上下注),同时也能够向代理付款。


增强型 AI 交易者:为交易者和投机者提供进阶操作的 DeFi 超级应用,包括:满足条件时进行 DCA 建仓;当 Gas 价格跌破特定价格时执行交易;监控新的 meme 代币合约;确定订单路由等。 


AI 代理的长尾:虽然 ChatGPT 等大型应用程序适合某些一般聊天目的,但 AI 代理需要针对众多行业、主题和利基市场。 Bittensor 等为「矿工」提供激励,围绕目标行业(例如加密货币、生物技术、学术界)为特定任务(例如图像生成、预训练、预测建模)训练模型。虽然 Bittensor 还处于萌芽阶段,开发人员已经在使用 Bittensor 在开源 LLM 基础上构建长尾应用程序。 


NPC 消费者应用代理:非玩家角色在 MMORPG 等游戏中很常见,但在多人消费者应用中不太常见。然而,加密消费者应用程序的金融化性质使人工智能代理成为引入新型游戏机制的优秀参与者。开放人工智能基础设施公司 Ritual 最近发布了 Frenrug,这是一个 Friend.tech 上基于 LLM 的代理,它将根据用户消息执行交易(购买或出售 key)。 Friend.tech 用户可以尝试说服代理购买他们的 key、出售其他人的 key,或者尝试让 Frenrug 代理以其他方式使用资金。 


随着越来越多的应用程序和协议使用人工智能代理,它们将作为人类访问加密经济的渠道。虽然人工智能代理今天看起来像玩具,但在未来,它们将增强日常消费者体验,成为协议的关键利益相关者,它们将创建整个加密经济体。 

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