据Coinfello数据,AI智能体可规避Robinhood的股票代币限制

cryptonews.ruPublished on 2026-08-03Last updated on 2026-08-03

Abstract

根据Coinfello的分析,AI代理可能绕开Robinhood对股票代币的限制。Robinhood Chain于7月1日上线,基于Arbitrum Nitro构建,专注于代币化现实资产和全天候交易。该网络采用由Robinhood控制的单一排序器。平台提供的股票代币是追踪如英伟达和特斯拉等公司股价的代币化债务证券,不附带股东权利,已在120多个国家上线,但根据证券法明确禁止美国居民交易。 Trust Wallet等第三方钱包已集成Robinhood Chain,用户可通过它们访问相同合约,绕过Robinhood应用本身。Coinfello联合创始人MinChi Park指出,这种界面级的区域封锁更多是发行方规避责任的手段,而非真正的监管执行,因为一旦使用第三方钱包,限制便消失。 Robinhood自身产品线也显示出监管执行的不一致:美国用户可以使用同一条链上的Robinhood Earn信贷产品,却无法访问近在咫尺的代币化股票。Park认为,监管附着于产品“包装”,而可组合性附着于资产本身,两者在链上存在矛盾。 2026年5月,Robinhood推出了多层代理交易,允许客户连接第三方AI代理来自动分析、交易和管理投资组合。专家担忧,AI代理消除了以往需要技术能力(如直接与合约交互)的非正式保护屏障,将复杂的合约调用简化为自然语言指令,使得受限用户更容易接触到受限产品,同时由于代理是非托管的,托管问题变得无关紧要。 真正的解决方案可能将合规检查编码到资产合约本身,而非依赖应用设置。例如,将代币的限制条件和风险披露直接写入智能合约,供钱包和代理读取并强制执行。目前Robinhood的股票代币已声明不提供投票权等,但这种披露需要在交易时明确提示。随着Robinhood Chain交易额突破90亿美元,所有接入的钱包和代理都将面临界面限制与底层合约权限之间的脱节问题。

在一众喧嚣与浮华中,Robinhood Chain网络于7月1日启动。该网络基于Arbitrum的Nitro堆栈构建,专为代币化的现实世界资产和24小时交易设计,它使用一个由Robinhood管理的单一排序器,且没有在未经许可的情况下切换至替代机制的路径。此外,即使底层智能合约对所有人开放,该公司似乎仍能直接控制交易的排序。

股票代币——这些由Robinhood Assets (Jersey) Limited发行、跟踪英伟达和特斯拉等公司股价但不赋予股东权利的代币化债务证券——已在超过120个国家可用,但根据证券法明确规定禁止美国居民购买。此外,就在最近,Trust Wallet已与Robinhood Chain集成——成为少数几个可以不通过Robinhood自家应用、直接访问相同合约的第三方钱包之一。

理论上,这样的整合看起来很完美,但受限产品与开放网络并行的这种割裂,似乎让许多业内人士感到不安,包括链上智能体平台Coinfello的联合创始人MinChi Park。她认为,界面层级的封锁是实际执法的薄弱替代品,并补充道:

界面层的地区封锁保护的是发行方。它对用户的保护要弱得多。这里有一个测试:如果限制在用户打开第三方钱包的那一刻就消失了,那么这从来就不是一个监管执行机制。那是一个责任盾牌。

基于资格的区分已然存在

Robinhood自家的产品线已经展示了这种执行是多么的不均衡:虽然股票代币对美国居民仍然不可用,但Robinhood Earn(一款基于Morpho的借贷产品,为USDG提供约7%的年化收益率)自上月初起,已开始向同一链上符合条件的美国客户开放。

Earn产品的发布覆盖了Robinhood的客户基础,即2770万拥有注资账户的客户,他们持有平台上的资产总额达3770亿美元,这意味着:美国用户可以在Robinhood Chain上向Morpho的池子提供贷款,同时却被禁止访问在同一钱包内仅一键之遥的代币化英伟达股票。Park断言,这种区分并非Robinhood日后会解决的启动阶段临时问题,她指出:

监管绑定在'包装'上,而可组合性绑定在资产上。这两样东西现在在同一条链上朝着相反的方向拉扯。

每个产品都有自己的发行方和司法管辖区边界,但是,当一个受限制的代币成为借贷市场的抵押品或通过聚合器流通时,这些边界就开始变得模糊。

AI智能体使情况复杂化的地方

2026年5月,Robinhood在这一结构中加入了多层级的智能体交易,允许客户通过公司的Model Context Protocol服务器连接第三方AI智能体,用于分析、交易和投资组合管理,无需人工干预。首席执行官Vlad Tenev将此举描述为,为零售用户提供了机构交易部门已经使用数十年的相同自动化工具。

然而,专家们担心,智能体会消除那些曾作为非正式保护措施的技术障碍。换言之,一个非托管的、可以将任何用户引向任何对象的智能体,不能被视作中立的实体,而是一个带有便捷用户界面的规避机制。

过去,直接访问受限合约需要找到地址、理解代码并手动管理密钥——这种技能门槛使得大多数受限用户无法接触到大多数受限产品。一个能将自然语言请求转化为多步骤合约调用的智能体,消除了这个障碍,同时从不托管用户的资产,Park认为这使托管问题变得无关紧要。

真正的限制执行可能是什么样子

一个解决方案可能是将合规检查直接内置于资产本身,而不是将其留在应用设置中。这意味着,限制将被直接编码在代币合约中,以一种钱包和智能体可以程序化读取和遵守的形式,并且智能体应在操作时刻显示披露信息,而不是绕过它们技术上可以读取的规则。

Robinhood自家的代币已经包含了一项值得在关键时刻披露的信息:例如,股票代币不提供投票权或股东权利,并且仅允许现金赎回——这种结构已经引发了关于买家实际拥有什么的单独讨论。

Robinhood或其DeFi合作伙伴是否会在链上实施这种级别的资格验证,其影响将远远超出这一条链。Robinhood Chain的交易量最近已超过90亿美元,每一个连接到它的钱包或智能体,都继承了界面层阻止什么与底层合约允许什么之间的相同割裂。

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Related Questions

Q根据Coinfello的观点,为什么Robinhood Chain在用户界面层面对美国居民进行的地理封锁被认为是薄弱的执法机制?

ACoinfello的联合创始人认为,界面层的地区封锁主要是为了保护发行商(Robinhood),对用户的保护则弱得多。关键在于,当用户打开一个第三方钱包时,限制就消失了,这说明该限制从来就不是一个有效的监管执行机制,而是发行商规避责任的一个屏障。

Q文章中提到Robinhood Chain内部存在什么矛盾?

ARobinhood Chain内部存在一个根本矛盾:一方面,监管要求将特定产品(如股票代币)与某些地区(如美国)的用户隔离开;另一方面,区块链的可组合性本质允许用户通过去中心化应用(如第三方钱包或AI代理)直接访问底层合约,绕开界面层的限制。这两股力量在同一条链上相互对抗。

QAI代理的引入如何使Robinhood Chain上的合规执行问题变得更加复杂?

AAI代理消除了普通用户访问底层智能合约所需的技术门槛(如查找合约地址、理解代码、管理私钥)。用户只需用自然语言发出指令,AI代理就能将其转化为多步骤的合约调用,从而让受地理限制的用户轻松绕过界面层的封锁,直接接触受限产品(如股票代币)。AI本身不托管用户资产,这使得传统以托管为抓手的监管思路失效。

Q文章提出了什么样的潜在解决方案来加强链上限制的真实执行?

A文章提出的一个潜在解决方案是将合规检查(如地理限制)直接编码到资产(代币)的智能合约逻辑中,而不是仅仅依赖于应用程序(前端)的设置。这样,无论用户通过何种钱包或AI代理访问该资产,这些限制都将在链上被强制执行,并且合规披露信息可以在用户执行操作的瞬间直接显示。

QRobinhood Chain上推出的股票代币(Stock Tokens)与真实的股票有何关键区别?

ARobinhood Chain上的股票代币是追踪如英伟达、特斯拉等公司股价的代币化债务证券,由Robinhood Assets (Jersey) Limited发行。关键区别在于,这些代币不赋予持有者任何股东权利(如投票权),并且发行人只提供现金赎回,不兑换为标的公司的实际股票。

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Its operational model is built around several key features: Human-like Computer Interaction: The framework offers advanced AI planning, striving to make interactions with computers more intuitive. By mimicking human behaviour in tasks execution, it promises to elevate user experiences. Narrative Memory: Employed to leverage high-level experiences, Agent S utilises narrative memory to keep track of task histories, thereby enhancing its decision-making processes. Episodic Memory: This feature provides users with step-by-step guidance, allowing the framework to offer contextual support as tasks unfold. Support for OpenACI: With the ability to run locally, Agent S allows users to maintain control over their interactions and workflows, aligning with the decentralised ethos of Web3. Easy Integration with External APIs: Its versatility and compatibility with various AI platforms ensure that Agent S can fit seamlessly into existing technological ecosystems, making it an appealing choice for developers and organisations. These functionalities collectively contribute to Agent S's unique position within the crypto space, as it automates complex, multi-step tasks with minimal human intervention. As the project evolves, its potential applications in Web3 could redefine how digital interactions unfold. Timeline of Agent S The development and milestones of Agent S can be encapsulated in a timeline that highlights its significant events: September 27, 2024: The concept of Agent S was launched in a comprehensive research paper titled “An Open Agentic Framework that Uses Computers Like a Human,” showcasing the groundwork for the project. October 10, 2024: The research paper was made publicly available on arXiv, offering an in-depth exploration of the framework and its performance evaluation based on the OSWorld benchmark. October 12, 2024: A video presentation was released, providing a visual insight into the capabilities and features of Agent S, further engaging potential users and investors. These markers in the timeline not only illustrate the progress of Agent S but also indicate its commitment to transparency and community engagement. Key Points About Agent S As the Agent S framework continues to evolve, several key attributes stand out, underscoring its innovative nature and potential: Innovative Framework: Designed to provide an intuitive use of computers akin to human interaction, Agent S brings a novel approach to task automation. Autonomous Interaction: The ability to interact autonomously with computers through GUI signifies a leap towards more intelligent and efficient computing solutions. Complex Task Automation: With its robust methodology, it can automate complex, multi-step tasks, making processes faster and less error-prone. Continuous Improvement: The learning mechanisms enable Agent S to improve from past experiences, continually enhancing its performance and efficacy. Versatility: Its adaptability across different operating environments like OSWorld and WindowsAgentArena ensures that it can serve a broad range of applications. As Agent S positions itself in the Web3 and crypto landscape, its potential to enhance interaction capabilities and automate processes signifies a significant advancement in AI technologies. Through its innovative framework, Agent S exemplifies the future of digital interactions, promising a more seamless and efficient experience for users across various industries. Conclusion Agent S represents a bold leap forward in the marriage of AI and Web3, with the capacity to redefine how we interact with technology. While still in its early stages, the possibilities for its application are vast and compelling. Through its comprehensive framework addressing critical challenges, Agent S aims to bring autonomous interactions to the forefront of the digital experience. As we move deeper into the realms of cryptocurrency and decentralisation, projects like Agent S will undoubtedly play a crucial role in shaping the future of technology and human-computer collaboration.

962 Total ViewsPublished 2025.01.14Updated 2025.01.14

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