Breaking Down Information Silos in Web3 With AI

AI-driven dashboards help aggregate data across multiple chains, giving users a more holistic view of the market, says Galxe's Charles Wayn.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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?

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.

Although the aforementioned tool may seem hypothetical, the fact of

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