利用 AI 打破 Web3 中的信息孤岛

Galxe 的 Charles Wayn 表示，人工智能驱动的仪表板有助于汇总多个链上的数据，让用户能够更全面地了解市场。

The decentralized nature of Web3 has led to a proliferation of independent networks, unique decentralized apps (dApps), and layer-reliant crypto projects, creating a fragmented ecosystem. As each new platform or chain is born, they ultimately add to a constantly expanding Web of isolated data. These pockets of information, often inaccessible and disconnected, are known as information silos.

Web3 的去中心化性质导致了独立网络、独特的去中心化应用程序 (dApp) 和层依赖的加密项目的激增，从而创建了一个碎片化的生态系统。随着每个新平台或链的诞生，它们最终都会添加到不断扩展的孤立数据网络中。这些信息块通常无法访问且互不相连，被称为信息孤岛。

For both seasoned degens and blockchain newcomers, these silos make it difficult to get a clear, comprehensive understanding of the Web3 market. But there is hope. By wielding nascent technologies like artificial intelligence (AI), pioneers of the decentralized front have the opportunity to tear down information silos to create a more connected and user-friendly ecosystem.

对于经验丰富的开发者和区块链新手来说，这些孤岛使得他们很难对 Web3 市场有一个清晰、全面的了解。但还有希望。通过运用人工智能（AI）等新兴技术，去中心化前沿的先驱者有机会打破信息孤岛，创建一个更加互联和用户友好的生态系统。

In a traditional, centralized system, data is stored and managed in one place. This makes it simple for machines running on the system to access information with ease. On the other hand, a major facet of blockchain technology is the storage of data and records across a distributed network, meaning blockchains have the potential to operate independently — each with its own network, rules, and data.

在传统的集中式系统中，数据在一个地方存储和管理。这使得系统上运行的机器可以轻松地访问信息。另一方面，区块链技术的一个主要方面是通过分布式网络存储数据和记录，这意味着区块链有独立运行的潜力——每个区块链都有自己的网络、规则和数据。

But this separation can lead to data being siloed: scattered across various platforms and chains without a simple way to connect them. To illustrate this disconnect, imagine you are a casual trader (and if you’re reading this, you very well might be). Because you hold assets of various types across a variety of chains you may regularly check in on one platform for token prices, a few others for analytics, and yet more still for project updates.

但这种分离可能会导致数据被孤立：分散在各种平台和链上，而没有简单的方法来连接它们。为了说明这种脱节，假设您是一名休闲交易者（如果您正在阅读本文，那么您很可能是一名休闲交易者）。由于您在各种链上持有各种类型的资产，因此您可以定期在一个平台上查看代币价格，在其他一些平台上查看分析，甚至更多地查看项目更新。

On top of that, you’re managing multiple wallets, interacting with an assortment of governance protocols, and tracking fees and tokenomics, all of which are fragmented across different networks. Making sense of this fragmentation can be downright overwhelming.

最重要的是，您需要管理多个钱包，与各种治理协议进行交互，并跟踪费用和代币经济，所有这些都分散在不同的网络中。理解这种碎片化的情况可能是令人难以承受的。

Of course, information silos are more than a simple inconvenience. They can have real consequences for users and the industry as a whole. One significant impact that information silos have on Web3 is raising the barrier of entry into the decentralized space. Web3 is already considered difficult to understand, especially for general consumers and those new to crypto. Information silos only make the learning curve steeper, forcing users to juggle multiple platforms, wallets, and tokens from the outset.

当然，信息孤岛不仅仅是一种简单的不便。它们可以对用户和整个行业产生真正的影响。信息孤岛对 Web3 的一项重大影响是提高了进入去中心化空间的门槛。 Web3 已经被认为难以理解，尤其是对于普通消费者和加密货币新手来说。信息孤岛只会让学习曲线变得更加陡峭，迫使用户从一开始就需要兼顾多个平台、钱包和代币。

Information silos can also create missed opportunities for users at every level. With so much information scattered across different platforms, it’s easy to miss out on key trends or investment opportunities. Without a way to quickly synthesize information from multiple sources, even the most experienced traders can miss the window to act on a promising new project or market shift.

信息孤岛还可能导致各个级别的用户错失机会。由于大量信息分散在不同的平台上，很容易错过关键趋势或投资机会。如果无法快速综合多个来源的信息，即使是最有经验的交易者也可能错过对有前景的新项目或市场转变采取行动的窗口。

Additionally, siloed information can be detrimental by increasing users’ exposure to scams. To consumers off-chain (and often to those on-chain, too) Web3 is notorious for hacks and scams Having access to reliable, consolidated information is crucial to avoiding these traps. But with data spread out across multiple chains and platforms, it’s hard to verify the legitimacy of new projects, creating dangerous blind spots in a fast-moving market.

此外，孤立的信息可能会增加用户遭受诈骗的风险，从而产生有害影响。对于链下消费者（通常也包括链上消费者）来说，Web3 因黑客和诈骗而臭名昭著，获得可靠、整合的信息对于避免这些陷阱至关重要。但随着数据分布在多个链和平台上，很难验证新项目的合法性，从而在快速变化的市场中造成危险的盲点。

If Web3’s goal is to make decentralized technology more accessible, we need to reduce this complexity, not add to it. With Web3’s (Surge-propelled) scalability paradigm continuing to grow, the need for better interoperability is becoming more critical. As L1, L2, and now even L3 “solutions” emerge poised to improve the capabilities of an already expansive system of blockchains, users and developers alike are finding it increasingly difficult to transact.

如果 Web3 的目标是让去中心化技术更容易使用，那么我们需要降低这种复杂性，而不是增加它。随着 Web3（Surge 推动的）可扩展性范例的不断发展，对更好的互操作性的需求变得越来越重要。随着 L1、L2 甚至现在的 L3“解决方案”的出现，准备提高已经广泛的区块链系统的功能，用户和开发人员都发现交易越来越困难。

Till now, measures like bridging and chain abstraction have seemed promising in mitigating the challenges of our fragmented blockchain landscape. But more recently, AI has emerged as a potential measure to combat the information silos that continue to pile up in Web3.

到目前为止，桥接和链抽象等措施似乎有望缓解分散的区块链环境的挑战。但最近，人工智能已成为对抗 Web3 中不断堆积的信息孤岛的潜在措施。

In our current ChatGPT-dominated tech landscape, AI has already found a foothold within a range of different industries. Although controversy still abounds when it comes to its application within the creative sector, it’s often favored by those in the crypto sphere for project development or automated trading.

在我们目前以 ChatGPT 为主的技术领域，人工智能已经在一系列不同的行业中找到了立足点。尽管在创意领域的应用仍然存在很多争议，但它经常受到加密货币领域的项目开发或自动交易的青睐。

Yet, considering a major function of AI is to automate and refine data aggregation, there may be a place for it in the endeavor of breaking down the barriers between isolated pockets of information. Speaking more specifically, consider the role that big data (data collections too large for traditional methods to process) plays in informing AI functionality. Now imagine this relationship being flipped, with AI taking the lead as a nontraditional way of analyzing immense and often disparate data sets.

然而，考虑到人工智能的主要功能是自动化和完善数据聚合，它在打破孤立信息之间的障碍的努力中可能有一席之地。更具体地说，请考虑大数据（对于传统方法来说太大而无法处理的数据集合）在为人工智能功能提供信息方面所发挥的作用。现在想象一下这种关系被翻转，人工智能率先成为分析巨大且通常不同的数据集的非传统方式。

Applied to information silos in Web3, we could conceive a tool that pulls together information from various blockchains, dApps, and exchanges into a single interface. And, taking that interface one step further, why not prompt such an AI aggregator to use this data to provide actionable insights to users?

应用于 Web3 中的信息孤岛，我们可以设想一种工具，将来自各种区块链、dApp 和交易所的信息汇集到一个界面中。而且，将该界面更进一步，为什么不促使这样的人工智能聚合器使用这些数据来为用户提供可操作的见解呢？

For traders looking to monitor market trends, such an AI interface could mitigate users' exposure to scams and the aforementioned missed opportunities that many face. Additionally, for newcomers, AI could make the Web3 landscape more approachable, effectively lowering the barrier to entry that a fragmented ecosystem presents.

对于希望监控市场趋势的交易者来说，这样的人工智能界面可以减少用户遭受诈骗的风险以及许多人面临的上述错失机会。此外，对于新来者来说，人工智能可以使 Web3 景观更加平易近人，有效降低分散的生态系统带来的进入壁垒。

Although the aforementioned tool may seem hypothetical, the fact of

尽管上述工具似乎是假设的，但事实是