利用 AI 打破 Web3 中訊息的孤島

Galxe 的 Charles Wayn 表示，人工智慧驅動的儀表板有助於匯總多個鏈上的數據，讓使用者更全面地了解市場。

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 的去中心化性質導致了獨立網路、獨特的去中心化應用程式 (dApp) 和層依賴的加密項目的激增，從而創建了一個碎片化的生態系統。隨著每個新平台或鏈的誕生，它們最終都會添加到不斷擴展的孤立數據網路中。這些資訊區塊通常無法存取且互不相連，稱為資訊孤島。

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.

對於經驗豐富的開發者和區塊鏈新手來說，這些孤島使得他們很難對 Web3 市場有一個清晰、全面的了解。但還有希望。透過運用人工智慧（AI）等新興技術，去中心化前沿的先驅者有機會打破資訊孤島，創造一個更互聯且用戶友好的生態系統。

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.

在傳統的集中式系統中，資料在一個地方儲存和管理。這使得系統上運行的機器可以輕鬆地存取資訊。另一方面，區塊鏈技術的一個主要方面是透過分散式網路儲存資料和記錄，這意味著區塊鏈有獨立運行的潛力——每個區塊鏈都有自己的網路、規則和資料。

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.

但這種分離可能會導致資料被孤立：分散在各種平台和鏈上，而沒有簡單的方法來連接它們。為了說明這種脫節，假設您是休閒交易者（如果您正在閱讀本文，那麼您很可能是休閒交易者）。由於您在各種鏈上持有各種類型的資產，因此您可以定期在一個平台上查看代幣價格，在其他一些平台上查看分析，甚至更多地查看項目更新。

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，您需要管理多個錢包，與各種治理協議進行交互，並追蹤費用和代幣經濟，所有這些都分散在不同的網路中。理解這種碎片化的情況可能是令人難以承受的。

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.

當然，資訊孤島不僅僅是一種簡單的不便。它們可以對用戶和整個行業產生真正的影響。資訊孤島對 Web3 的一項重大影響是提高了進入去中心化空間的門檻。 Web3 已經被認為難以理解，尤其是對於普通消費者和加密貨幣新手來說。資訊孤島只會讓學習曲線變得更加陡峭，迫使用戶從一開始就需要兼顧多個平台、錢包和代幣。

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.

資訊孤島也可能導致各個層級的用戶錯失機會。由於大量資訊分散在不同的平台上，很容易錯過關鍵趨勢或投資機會。如果無法快速綜合多個來源的信息，即使是最有經驗的交易者也可能錯過對有前景的新項目或市場轉變採取行動的窗口。

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，孤立的資訊可能會增加用戶遭受詐騙的風險，從而產生有害影響。對於鏈下消費者（通常也對鏈上消費者而言）來說，Web3 因駭客和詐騙而臭名昭著，獲得可靠、整合的資訊對於避免這些陷阱至關重要。但由於數據分佈在多個鍊和平台上，很難驗證新項目的合法性，從而在快速變化的市場中造成危險的盲點。

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 的目標是讓去中心化技術更容易使用，那麼我們需要降低這種複雜性，而不是增加它。隨著 Web3（Surge 推動的）可擴展性範式的不斷發展，對更好的互通性的需求變得越來越重要。隨著 L1、L2 甚至現在的 L3「解決方案」的出現，準備提高已經廣泛的區塊鏈系統的功能，用戶和開發人員都發現交易越來越困難。

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.

到目前為止，橋接和鏈抽像等措施似乎有望緩解分散的區塊鏈環境的挑戰。但最近，人工智慧已成為對抗 Web3 中不斷堆積的資訊孤島的潛在措施。

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.

在我們目前以 ChatGPT 為主的技術領域，人工智慧已經在一系列不同的產業中找到了立足點。儘管在創意領域的應用仍然存在著許多爭議，但它經常受到加密貨幣領域的專案開發或自動交易的青睞。

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，考慮到人工智慧的主要功能是自動化和完善資料聚合，它在打破孤立資訊之間的障礙的努力中可能有一席之地。更具體地說，請考慮大數據（對於傳統方法來說太大而無法處理的數據集合）在為人工智慧功能提供資訊方面所發揮的作用。現在想像一下這種關係被翻轉，人工智慧率先成為分析巨大且通常不同的資料集的非傳統方式。

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?

應用於 Web3 中的資訊孤島，我們可以設想一種工具，將來自各種區塊鏈、dApp 和交易所的資訊匯集到一個介面中。而且，將該介面更進一步，為什麼不促使這樣的人工智慧聚合器使用這些數據來為用戶提供可操作的見解呢？

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.

對於希望監控市場趨勢的交易者來說，這樣的人工智慧介面可以減少用戶遭受詐騙的風險以及許多人面臨的上述錯失機會。此外，對於新來者來說，人工智慧可以使 Web3 景觀更加平易近人，有效降低分散的生態系統所帶來的進入障礙。

Although the aforementioned tool may seem hypothetical, the fact of

儘管上述工具似乎是假設的，但事實是