Galxe Co-Creation: Using AI to break the information silos in Web3

Author: Galxe co-founder Charles Wayn, CoinDesk; Translator: Deng Tong, Golden Finance

The development of Web3 is completely unpredictable. From the humble beginnings of Bitcoin, to the ICO boom, the emergence of Ethereum, to DeFi and NFT, technicians have always firmly believed in the power of blockchain technology to drive future innovation.

However, the decentralized nature of Web3, which is often seen as its greatest advantage, has become a source of complexity in recent years. The current state of the blockchain industry, characterized by the proliferation of independent networks, unique decentralized applications, and layer-dependent crypto projects, has created a fragmented ecosystem.

With the birth of each new platform or chain, they eventually form an ever-expanding network of isolated data. These blocks of information are often inaccessible and unconnected, known as information islands.

For experienced developers and blockchain newcomers, these islands make it difficult for them to have a clear, comprehensive understanding of the Web3 market. But there is hope. By applying emerging technologies like AI, pioneers on the decentralization frontier have the opportunity to break down information silos and create a more connected and user-friendly ecosystem.

Information Silos in Web3

In traditional centralized systems, data is stored and managed in one place. This allows machines running on the system to easily access information.

On the other hand, one of the main aspects of blockchain technology is the storage of data and records across a distributed network, which means that 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 with no easy way to connect them.

To illustrate this disconnect, let's say you're a casual trader (and if you're reading this, you're most likely one). Since you hold various types of assets on various chains, you may regularly check token prices on one platform, analytics on a few others, and even more for project updates.

On top of that, you need to manage multiple wallets, interact with various governance protocols, and keep track of fees and token economics, all scattered across different networks. Making sense of this fragmentation can be overwhelming.

The Consequences of Fragmentation

Of course, information silos are more than just a simple inconvenience. They can have real consequences for users and the industry as a whole.

One major impact that information silos have on Web3 is that they raise the barrier to entry into the decentralized space. Web3 is already considered difficult to understand, especially for the average consumer and crypto newbies. Information silos only make the learning curve steeper, forcing users to juggle multiple platforms, wallets, and tokens from the get-go.

Information silos can also lead to missed opportunities for users of all levels. With so much information scattered across different platforms, it’s easy to miss key trends or investment opportunities. Without the ability to quickly synthesize information from multiple sources, even the most experienced traders can miss the window to act on promising new projects or market shifts.

In addition, siloed information can have a detrimental effect by increasing users’ risk of scams.

For off-chain consumers (and often on-chain consumers as well), Web3 is notorious for hacks and scams. Access to reliable, consolidated information is essential to avoiding these pitfalls. But with data spread across multiple chains and platforms, it’s difficult to verify the legitimacy of new projects, creating dangerous blind spots in a rapidly changing market.

If Web3’s goal is to make decentralized technology easier to use, then we need to reduce this complexity, not increase it.

Breaking Down Information Silos

As the scalability paradigm of Web3 (driven by Surge) continues to evolve, the need for better interoperability becomes increasingly important. As L1, L2, and now even L3 “solutions” emerge, ready to increase the functionality of already widespread blockchain systems, users and developers alike are finding it increasingly difficult to transact.

So far, measures like bridging and chain abstraction have seemed promising to ease the challenges of a fragmented blockchain environment. But more recently, AI has emerged as a potential countermeasure to the growing pile-up of information silos in Web3.

In our current tech landscape dominated by ChatGPT, AI has found a foothold in a range of different industries. While its application in the creative sector remains much debated, it is often favored for project development or automated trading in the cryptocurrency space.

However, given that AI’s primary function is to automate and refine data aggregation, it may have a place in efforts to break down barriers between siloed information.

The Case for AI in Web3 De-Siloing

More specifically, consider the role that big data (collections of data that are too large for traditional methods to handle) has played in informing AI capabilities. Now imagine this relationship is flipped, with AI taking the lead as a non-traditional way to analyze huge and often disparate data sets.

Applied to information silos in Web3, we can envision a tool that brings together information from various blockchains, dApps, and exchanges into a single interface. And, taking that interface a 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 AI interfaces could reduce users’ risk of scams and the aforementioned missed opportunities that many face. Additionally, for newcomers, AI could make the Web3 landscape more approachable, effectively lowering the barriers to entry that come with a fragmented ecosystem.

Be skeptical of AI’s role in Web3

While the aforementioned tools may seem hypothetical, the fact is that AI interfaces for combating information silos already exist.

In addition, we’ve already begun to see the impact of AI adoption in Web3, with numerous platforms vying for AI supremacy in security, defragmentation, and analytics. Even at the most basic user level, AI-powered dashboards help aggregate data across multiple chains, allowing users to gain a more holistic view of the market.

However, while Web3 may seem to promote AI, it’s important to take its transformative potential with a grain of salt. We’ve already witnessed many instances of AI hallucinations being worrisome, if not harmful — Google AI’s recent search debacle perfectly demonstrated this.

On paper, AI certainly has the power to create a more seamless and user-friendly Web3 ecosystem. Especially when combined with concepts like chain abstraction, AI could be the key to driving the mass adoption that decentralized maximalists dream of.

However, while advances in AI may show promising progress in its ability to aid defragmentation, as with anything in Web3, it’s critical for DYORs to get in early and approach any potential automation revolution with a healthy dose of skepticism.