With the overwhelming presence of AI, particularly AIGC platforms like ChatGPT and Midjourney, it’s intriguing to think how many still remember Web3 amidst this tidal wave of news. Recently, subjects like blockchain, cryptocurrency, DeFi, and NFT have been dismissed as “outdated topics.” Still, the concerns AI has recently sparked—such as the explosion in content, the authenticity of information, intellectual property tracking, and privacy breaches—could be aptly tackled using blockchain. On one side, we have AI-generated content, which is fast, accessible, technically optimized, and growing exponentially, yet plagued with authenticity and ownership concerns. On the other, there’s Web3—decentralized, emphasizing asset ownership, immutable, traceable, but slower and more challenging for the general populace. These seemingly opposing technologies can complement each other, driving the next wave of technological advancements.

What’s This Old-School Analogy?

Coming back to the title, why this old-school analogy? Why does AI remind me of Sun Wukong and Web3 of Tang Sanzang? Sun Wukong is sharp and adaptable. Faced with any opponent, he quickly identifies patterns and devises strategies, much like AI. His 72 transformative abilities mirror the capabilities of AIGC to imitate, produce, and transform content—rapid, versatile, and strikingly accurate. Yet, AI can sometimes mimic Sun Wukong’s mischievousness, skirting on the edge and behaving unpredictably. On the other hand, Tang Sanzang is sincere, transparent, and principled, though sometimes overly naïve and stubborn, much like Web3 and blockchain. For the vast and unpredictable AI, the principles of blockchain serve as the restraining tiara on Sun Wukong’s head—unyielding rules ensuring behaviors don’t cross boundaries, always controllable and traceable. If you can think of other suitable analogies, feel free to share in the comments!

Recent Observations on Potential Blockchain Use Cases

Metaverse Content

Whether it’s Decentraland or Sandbox, these metaverse worlds have witnessed celebrities and enterprises scrambling to buy virtual land in an investment frenzy. However, anyone who’s ventured into these virtual realms would probably feel they are somewhat empty.

Whether these celebrities genuinely see potential in the metaverse and stake their claims or it’s just promotional hype by metaverse developers, many of these so-called “celebrity-owned lands” remain barren. Players shouldn’t hold out hope for any virtual interaction with their idols. Apart from the rare “virtual concerts” or “virtual fashion shows”, the metaverse mostly seems deserted.

Headline: The Loneliest Metaverse: A virtual world once valued at over $1.3 billion now sees only 38 active users daily.

Headline: EU’s $12 million “Metaverse Party” Debacle Exposed: Only 6 attendees, one of whom was a journalist.

Why? Simply put, it’s just too boring.

The lack of tools, events, interactive characters, and attractions is evident. Even conceding that, the barren plots, rudimentary architecture, and pixelated characters and outfits feel outdated, especially to a generation accustomed to 4K graphics. However, all this can be quickly set up through AIGC. Rich content in the metaverse, such as NPCs (Non-Player Characters) that can converse as naturally as real humans, could transform the experience. Incorporating AI-driven stories, events, scenarios, and personalized avatars and costumes would make even a single-player game intriguing. Adding social interaction, celebrity involvement, and online-to-offline elements could truly make the metaverse attractive to both gamers and the general public.

Environmental Conservation and Efficiency

Generative AI can be used to produce compressed data, reducing storage space and transmission costs on the blockchain. As Nvidia CEO Jensen Huang said:

Headline: “…The greater the computational power, the higher the costs and energy consumption. If our advanced tech-driven world relies solely on this computational power, it won’t only strain our finances, but the planet wouldn’t be able to bear it.”

Huang explained that this is why NVIDIA spent 30 years developing accelerated computing to address such issues. With the advent of AI, simulations can reduce computational requirements by factors of tens of thousands. For instance, a dog, without understanding physics or gravity, can predict where a ball will land and catch it. It relies on innate “skills” rather than calculating the physical event. The same concept applies to AI. By teaching AI the laws of physics, computational needs can be reduced, leading to significant energy savings.

“The saved energy and computational power is not just eco-friendlier, but it also frees up capacity for new technological advancements,” Huang added, “anticipating a new leap in the world of technology.”

NFT Tickets

This is an increasingly discussed topic. NFTs, as ticketing mechanisms, can deter scalping, enhance collectability, create secondary revenue streams for organizers, and offer loyalty point systems. Here, AI’s role becomes pivotal in detecting unique scalping patterns, flagging suspicious accounts, and auto-generating unique designs and messages for each ticket.

A recent news article highlighted Ticketmaster, the world’s largest ticketing system, introducing NFT ticketing services on the Flow blockchain. This allows event organizers to attach NFTs to tickets, offering ticket holders exclusive VIP experiences or access to Web3 versions of events.

Source: Ticketmaster Takes A Huge Step Toward NFT Tickets.

Insurance/Claims

Insurance companies both domestically and internationally have long utilized blockchain to enhance their efficiency. For instance, Cathay’s “Property Insurance Alliance Chain” connects 14 domestic property insurance companies and has garnered the support of the financial regulatory commission. This aids in the digital transformation of the property insurance sector using blockchain technology.

For a common issue within the insurance industry, such as insurance fraud, by uploading each insurer’s policy data onto a blockchain, the alliance chain can help companies interlink their data. This prevents problems like duplicate insurance coverage and claims. Additionally, it simplifies the procedure for shared claims. Historically, if two vehicles collided, one insurance company would have to initiate the compensation process, followed by the other company reimbursing them. This process required manual paper exchanges and data entry by insurance staff, usually taking up to 90-100 hours each month.

With AI, this process can transition from being “digitized” to “automated,” reducing human error and time consumption. Collaboration between companies becomes faster, and user personal information remains more confidential. In the future, AI can also design personalized products based on a user’s age, social interactions, health, and other factors. This creates a comprehensive and fully automated process.

Another example comes from Shin Kong Life Insurance. In collaboration with SAS, they developed a claim fraud risk prediction system. By integrating AI into the claims process, every claim request automatically receives a risk assessment score, thus reducing human judgment errors. Fraud detection rates have increased to 15%, curtailing wasteful claim payouts.

Using AI can also help detect claim fraud risks. In the future, by gathering user social graphs, online behavior, mobile device information, and even past search keywords and content analysis, insurance companies can delve deeper into understanding a user’s identity and risk assessment.

Intellectual Property Rights + DAO & Content Origin and Tracking

In essence, the technology behind AIGC is legitimate, but concerns arise about the potential unauthorized use of the image databases these AI systems access. Legally speaking, does content generated by AI hold intellectual property rights? If so, who owns them? And if AIGC infringes on someone’s rights, who is accountable?

A recent article from TinTinLand proposes a solution: A DAO model formed by multiple stakeholders can manage AIGC platforms. It brings creators, original artwork owners, AIGC operators, and blockchain validators into four distinct roles. The creator’s earnings can be shared with the other three parties, determined by regular voting rights. In this structure, commercial value originates from the creator and is allocated to the original artwork owner, AIGC operator, and blockchain. All these stakeholders can integrate into a DAO via Web3, making AIGC usage and communication more efficient.

Using an advertising platform as an example, the DAO+AIGC management path can be seen as:

• Specialized marketing copy AIGC generates content and input value, aiding routine or specialized design work.

• After an advertisement copy owner uploads their work, they wait for it to be verified as an NFT, securing copyrights and benefits.

• AIGC operators can join the DAO, governing via advertisement copy voting and proposals, and participate in distribution.

• Blockchain validators cater to the entire system’s validation needs, ensuring fairness and transparency.

Apart from using DAO to link all stakeholders, blockchain’s transparent, traceable, and immutable mechanism aids in realizing shared benefits. Companies have also tried to benefit original content producers directly from the “AI model” source. For instance, Shutterstock and Getty Images, two of the world’s largest online image databases, collaborated with Nvidia via “AI Foundations” to develop their large language models.

Nvidia stated that creative software like Adobe, online image libraries such as Shutterstock and Getty Images, have already used “AI Foundations” to establish their large language models. Among them, Nvidia’s partnership with Getty Images focuses on creating responsible models. Since models converting images to text might infringe on artists’ rights, preventing them from receiving economic benefits, they’re developing a new model allowing artists to profit when their work is used.

Conclusion

There are many more case studies and ideas to consider. While researching and writing, one constantly stumbles upon or generates intriguing thoughts. Essentially, AI and Web3, which might seem contradictory at first, can complement each other, heralding a new era of technological progress for humanity. Just like the pairing of Sun Wukong and Tang Sanzang from the classic Chinese novel, AI and Web3 represent flexibility and stability, respectively, but when combined, achieve better results. As these two domains continuously evolve and merge, we hope to witness more innovative applications, transforming human lifestyles and work methodologies.

Statement:

1. This article is reprinted from Blockchain D World, and the copyright belongs to the original author [Uncle D]. If you have any objections to the reprint, please contact the Gate Learn team(gatelearn@gate.io). The team will process it as soon as possible according to the relevant procedures.
2. Disclaimer: The views and opinions expressed in this article only represent the author’s personal opinions and do not constitute any investment advice.
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