Hope to open up more discussions in the industry: which are feasible, what challenges remain to be solved, and how might the future evolve.

Authors: Scott Duke Kominers, Sam Broner, Jay Drain, Guy Wuollet, Elizabeth Harkavy, Carra Wu, and Matt Gleason

Translation: Aki Wu on Blockchain

The economic structure of the internet is changing. As open networks gradually collapse into a "prompt bar," we must consider: will AI lead to a more open internet, or will it trap us in a maze of new paywalls? And who will control the future internet — large centralized companies, or a broad user community?

This is where cryptographic technology comes into play. We have discussed the intersection of AI and cryptographic technology multiple times in the past, but in short, blockchain is a way to redesign internet services and network architecture, enabling the construction of decentralized, trust-neutral systems that can be "owned" by users. By reshaping the economic incentives behind today's systems, blockchain provides a counterbalance to the increasingly centralized trends in AI systems, thus promoting a more open and resilient internet.

The idea that "cryptographic technology can help build better AI systems, and vice versa" is not new — but it has long lacked a clear definition. Certain intersectional areas (such as how to verify "human identity" in the context of a surge in low-cost AI systems) have attracted a large number of developers and users. However, other application scenarios may still take years or even decades to materialize. Therefore, this article shares 11 intersectional applications of AI and cryptographic technology, hoping to spark more discussions in the industry: which are feasible, what challenges remain to be solved, and how might the future evolve.

These scenarios are based on technologies currently under development — from processing a large number of micro-payments to ensuring that humans retain ownership in their future relationships with AI.

1. Introducing Persistent Data and Context in AI Interactions

Scott Duke Kominers: Generative AI fundamentally relies on data, but in many application scenarios, "context" — the state and background information related to interactions — is often equally important, if not more critical, than the data itself.

Ideally, whether it’s an agent, LLM interface, or other types of AI applications, they should be able to remember a wealth of personalized information, including the types of projects you are working on, your communication habits, preferred programming languages, and more. However, in reality, users often have to repeatedly reconstruct this context — not only do they need to re-establish context when starting new sessions within the same application, such as opening a new ChatGPT or Claude window, but they also face challenges when switching between different AI systems.

Currently, context from one generative AI application is almost impossible to transfer to another application.

With blockchain, AI systems can store key contextual elements as persistent digital assets, allowing them to be loaded at the start of a session and seamlessly transferred between different AI platforms. Moreover, since "forwards-compatibility" and "interoperability commitments" are core features of blockchain protocols, blockchain may be the only technology path capable of systematically addressing this issue.

An intuitive application scenario is in AI-driven gaming and media, where user preferences (such as difficulty, key layouts, etc.) can persist across games and environments. However, the truly high-value scenarios are knowledge-based applications — AI needs to understand the knowledge systems, learning styles, and capabilities that users possess; as well as more specialized application scenarios, such as programming assistance. Although some companies have built customized AI tools with "global context" for their own businesses, this context still cannot be effectively transferred between different AI systems used within the organization.

Various organizations are just beginning to truly recognize this issue, and the closest thing to a universal solution currently is customized bots with fixed, persistent context. However, the portability of context between users within a platform has gradually emerged off-chain; for example, on the Poe platform, users can rent out their custom bots to other users.

If such activities were migrated on-chain, the AI systems we interact with would be able to share a context layer composed of key elements from all our digital behaviors. AI could instantly understand our preferences, allowing for better fine-tuning and experience optimization. Conversely, mechanisms similar to on-chain intellectual property registration systems, if they allow AI to reference on-chain persistent context, could give rise to new, more refined market interaction models around prompts and information modules — for instance, users could directly monetize their professional skills while maintaining data self-management.

Of course, as the ability to share context improves, it will also give rise to numerous new use cases and possibilities that are currently unforeseen.

2. A Universal Identity System for Agents

Sam Broner: Identity — the standardized record of "who" or "what" an object is — is the underlying infrastructure supporting today’s digital discovery, aggregation, and payment systems. However, because platforms keep this "underlying pipeline" closed within their systems, users typically experience identity systems only through a finished product interface. For example, Amazon assigns identifiers (like ASIN or FNSKU) to products, integrates them into a unified interface, and helps users with discovery and payment; Facebook operates similarly: user identity determines the content of their information feed and forms the basis for discovering various content within the app, including Marketplace listings, organic content, and advertisements.

With the rapid evolution of AI agents, this landscape is about to change. More and more companies are using agents for customer service, logistics, payments, and other scenarios, and their platforms will no longer be traditional "single interface applications," but will be distributed across multiple channels and platforms, continuously accumulating deep context and performing more tasks for users. However, if an agent's identity is only tied to a single platform or market, it will be difficult to use in other critical environments (such as email threads, Slack channels, or within other products).

Therefore, agents need a unified, portable "digital passport." Without it, there is no way to confirm how to pay the agent, verify its version, query its capabilities, identify who it represents in performing tasks, or track its reputation across applications and platforms. The identity system for agents must simultaneously function as a wallet, API registry, change log, and social reputation proof, allowing any interface (whether email, Slack, or other agents) to consistently interpret and communicate with it.

In the absence of such a shared "identity primitive," every system integration would require rebuilding this pipeline from scratch; content discovery would remain in a temporary patchwork state; and users would continuously lose their key context when switching between different channels and platforms.

We now have the opportunity to design agent infrastructure from "first principles." The question is: how do we build an identity layer that is richer than DNS records and possesses trusted neutrality? Rather than recreating a monolithic platform that bundles identity, discovery, aggregation, payment, and other functions together, it would be better to enable agents to autonomously receive payments, publicly disclose their capability lists, and exist across multiple ecosystems without the fear of being locked into a single platform.

This is precisely where the intersection of cryptographic technology and AI can play a role — blockchain networks provide permissionless composability, allowing developers to create more powerful agents and more user-friendly experiences.

Overall, user experiences with vertically integrated solutions like Facebook and Amazon are currently better — the reason being that one of the complexities of building excellent products is ensuring that all components naturally work together from the top down. However, the cost of this convenience is becoming increasingly high, especially against the backdrop of declining software costs required to build, aggregate, promote, commercialize, and distribute agents, as well as the expanding reach of agent applications.

Achieving the user experience of a vertically integrated platform still requires significant effort, but once a trusted neutral identity layer for agents is built, entrepreneurs can truly have their own passports. This will also drive widespread experimentation and innovation in distribution models and interaction design.

3. Future-Oriented Proof of Personhood (PoP)

Jay Drain Jr. and Scott Duke Kominers: With the proliferation of AI — whether it’s robots and agents running in various web interactions, or deepfakes and social media manipulation — it is becoming increasingly difficult to determine whether the entities we interact with online are real humans. This erosion of trust is not a future concern; it is a reality that is happening now. From comment bots on X to automated accounts on dating apps, the line between real and fake is becoming blurred. In such an environment, "proof of personhood" is gradually becoming a key infrastructure of the internet.

One way to verify "you are human" is through digital identity, including centralized identity verification systems used by agencies like the TSA. Digital IDs encompass all information users can use to prove their identity — usernames, PIN codes, passwords, and third-party certifications (such as nationality, credibility, or credit status). The value of decentralization here is very clear: when identity data is stored in centralized systems, issuers can revoke access, charge fees, or even assist in monitoring. Decentralization disrupts this structure: users, rather than platforms, control their identities, making them more secure and resistant to censorship.

Unlike traditional identity systems, decentralized proof of personhood mechanisms (such as Worldcoin's World’s Proof of Human) allow users to manage their identity data autonomously and verify that they are indeed "human" in a privacy-preserving, trust-neutral manner. Similar to a driver's license — which can be used in any scenario regardless of when or where it was issued — decentralized PoP can serve as a universal underlying foundational module that can be reused across any platform, including those that do not yet exist. In other words, blockchain-based PoP possesses "forwards-compatibility" because it provides:

Portability: The protocol is an open standard that any platform can integrate. Decentralized PoP can be managed through public infrastructure and is fully controlled by users. This means PoP inherently possesses portability, and any platform now or in the future can be compatible with it.

Permissionless Accessibility: Platforms can choose whether or not to support a particular PoP identity without undergoing centralized API approval that may impose discriminatory restrictions on different use cases.

The core challenge in this field is "adoption." Currently, there are no large-scale applications of "Proof of Personhood" (PoP) in the real world, but we expect that once the user base reaches a critical mass, several early partners emerge, and "killer applications" that drive user demand appear, the adoption of PoP will accelerate significantly. Every application that adopts a certain digital ID standard will enhance the value of that ID type to users; in turn, this will drive more users to obtain that ID; and a larger user base will increase the attractiveness of applications integrating that ID standard to verify "personhood." (Additionally, because on-chain IDs are designed to be interoperable, this network effect can spread rapidly.)

We have already seen mainstream consumer applications in gaming, dating, and social media announce partnerships with World ID to ensure that users are indeed interacting with real humans — even with specific individuals they expect. At the same time, new identity protocols have emerged this year, such as the Solana Attestation Service (SAS). Although SAS itself is not a PoP issuer, it allows users to privately associate off-chain data (such as KYC results required for compliance, investor certification qualifications, etc.) with their Solana wallet, thereby building a decentralized identity for users. These signs indicate that the turning point for decentralized PoP may not be far off.

The significance of Proof of Personhood goes far beyond "stopping bots." It aims to establish clear boundaries between AI agents and human networks, enabling users and applications to distinguish between different interactions of "humans and machines," thereby creating conditions for higher quality, safer, and more authentic digital experiences.

4. Decentralized Physical Infrastructure for AI (DePIN)

Guy Wuollet: Although AI is a digital service, its development is increasingly constrained by physical infrastructure. Decentralized Physical Infrastructure Networks (DePIN) — a new model for building and operating real-world systems — hold the promise of democratizing the computational infrastructure that supports AI innovation, making it cheaper, more resilient, and more resistant to censorship.

Why? The two main bottlenecks in AI development are energy and chip acquisition capabilities. Decentralized energy systems can provide more abundant power, while developers are also integrating idle chips from gaming PCs, data centers, and other sources using DePIN. These computing devices can collectively form a permissionless computational market, creating a fair competitive environment for building new AI products.

Other application scenarios include distributed training and fine-tuning of large language models (LLMs) and building distributed inference networks (model inference). Decentralized training and inference can significantly reduce costs because they utilize computational resources that would otherwise be idle. At the same time, such architectures possess inherent resistance to censorship, ensuring that developers are not "delisted" or restricted from access due to reliance on hyperscalers (centralized cloud infrastructure providers that offer large-scale, scalable computing resources).

The concentration of AI models in a few companies has long been a concern; decentralized networks can help build AI systems that are cheaper, more resistant to censorship, and more scalable.

5. Establishing Infrastructure and Security Mechanisms for Interactions Between AI Agents, Endpoint Service Providers, and Users

Scott Duke Kominers: As AI tools continue to enhance their capabilities in handling complex tasks and executing multi-layered interaction chains, AI will increasingly need to collaborate independently with other AIs without direct human control.

For example, an AI agent may need to request specific data required for a computation or call upon other agents with specialized capabilities to perform tasks — such as having a statistical analysis agent responsible for building and running model simulations, or engaging an image generation agent to assist in creating marketing materials. AI agents will also create significant value in end-to-end transaction execution, such as completely replacing users in completing a transaction process: finding and booking flights based on preferences or automatically discovering and purchasing new books that match user preferences.

Currently, there is no "universal agent-to-agent market." Such cross-agent requests can typically only be achieved through explicit API calls or are limited to certain closed AI agent ecosystems for internal functionality.

More broadly, most AI agents currently operate in isolated ecosystems: APIs are relatively closed, lacking unified architectural standards. Blockchain technology can help protocols establish open standards, which is crucial for short-term adoption; in the long term, this also aids in achieving forwards compatibility: as new types of agents continue to emerge, they can all connect to the same underlying network. Because blockchain possesses interoperable, open-source, decentralized, and often more easily upgradable architectures, it is better suited to adapt to changes brought about by future AI innovations.

Several companies are already building on-chain infrastructure for agent interactions. For example, Halliday recently launched a protocol that provides a standardized cross-chain architecture for AI workflows and interactions, while incorporating protective mechanisms at the protocol level to ensure that AI does not act beyond user intent. On the other hand, projects like Catena, Skyfire, and Nevermind leverage blockchain to support automatic settlements between agents, enabling AI-to-AI payments without any human intervention. Similar systems are continuously emerging, and Coinbase has also begun providing infrastructure support for such developments.

6. Keeping AI "Vibe Coding" Applications in Sync

Sam Broner and Scott Duke Kominers: The revolution in generative AI has made software development unprecedentedly easy. Coding speed has increased by orders of magnitude, and more importantly, coding can now be done directly through natural language, allowing inexperienced developers to replicate existing programs or even build new applications from scratch.

However, while AI-assisted coding creates new opportunities, it also introduces a significant amount of "entropy" within and across programs. The so-called "vibe coding" abstracts away the complex dependencies behind software — but because of this, when the underlying source code or inputs change, programs may expose risks in functionality and security. At the same time, as people use AI to create highly personalized applications and workflows, their integration with others' systems becomes more challenging. In fact, even if two vibe-coded programs perform nearly the same task, their operational logic and output structures may be completely different.

Traditionally, the standardization work to ensure consistency and compatibility has been handled by file formats, operating systems, and later shared software and API integrations. But in a world where software evolves, morphs, and branches in real-time, the standardization layer must possess: broad accessibility, continuous upgradability, and user trust. Moreover, relying solely on AI does not solve the incentive mechanism problem — that is, how to incentivize developers to build and maintain links between these systems.

Blockchain can address both of these challenges simultaneously by providing a protocolized synchronization layer that is embedded in user-customized software builds and can dynamically update with environmental changes to ensure cross-system compatibility.

In the past, large enterprises might have needed to pay millions of dollars to system integrators like Deloitte to customize a Salesforce instance. Today, an engineer might only need a weekend to build a custom interface for "sales data viewing." However, as the number of customized software applications continues to grow, developers will need assistance to ensure these applications remain synchronized and usable.

This is similar to the development model of today's open-source software libraries, but the difference is that the synchronization layer does not rely on periodic version releases but rather on continuous updates — and it also comes with incentive mechanisms. Both points can be more easily achieved through cryptographic technology. Like other blockchain-based protocols, shared ownership of the synchronization layer can incentivize all parties to continuously invest resources for improvement. Developers, users (and their AI agents), and other users can be rewarded for introducing, using, or iterating on new features and integration solutions.

Conversely, shared ownership also gives all users a vested interest in the overall success of the protocol, forming a deterrent mechanism against behavioral deviations. Just as Microsoft would not easily undermine the .docx file format standard, as it would have widespread negative impacts on its users and brand; synchronization layer co-owners would also be reluctant to introduce clunky or malicious code into the protocol due to their own interests being harmed.

Like all previous software standardization architectures, there is also significant potential for powerful network effects here. As AI-generated software experiences a "Cambrian explosion," the diverse and heterogeneous systems that need to communicate with each other will grow exponentially. In short: for vibe coding to stay in sync, it cannot rely solely on the vibe itself; cryptographic technology is the answer.

7. Micro-Payment Systems Supporting Revenue Sharing

Liz Harkavy: AI agents and tools like ChatGPT, Claude, and Copilot provide a more convenient way for people to access information in the digital world. However, for better or worse, they are also shaking the economic structure of the open internet. This trend has already become apparent — for example, as students increasingly use AI tools, educational platforms are experiencing significant declines in traffic; meanwhile, several media outlets in the U.S. have sued OpenAI over copyright infringement issues. If the incentive system cannot be readjusted, we may see the internet become even more closed, with more paywalls and a continued decrease in content creators.

Policy measures certainly always exist, but during the progression of judicial procedures, some technical solutions are also emerging. Among them, the most promising (and technically challenging) solution is to embed a "revenue-sharing mechanism" into the underlying architecture of the internet. When an AI-driven operation ultimately leads to a sale, the content creator providing the information source for that decision should receive a share of the revenue. Affiliate marketing ecosystems are already doing similar attribution tracking and revenue sharing; more advanced systems could automatically track all contributors along the information chain and reward them. Blockchain can clearly play a key role in tracking the "information source chain."

However, to realize such a system, new infrastructure is needed — particularly: a micro-payment system capable of handling tiny amounts between multiple sources; attribution protocols that can fairly assess the value of different contributions; and governance models that ensure transparency and fairness.

Many existing blockchain tools show potential, such as various rollups, L2 networks, AI-native financial institutions like Catena Labs, and financial infrastructure protocols like 0xSplits, all of which can achieve near-zero-cost transactions and more granular payment splits.

Blockchain can enable advanced payment systems dominated by agents through various mechanisms:

Nano Payments: Can be split among multiple data providers, allowing a single user interaction to automatically trigger micro-payments to all contributing sources, executed by smart contracts.

Smart Contracts: Can automatically trigger enforceable "post-payment" after a transaction is completed, providing transparent and traceable compensation to content sources that influenced purchasing decisions.

Programmable Payment Splits: Enable revenue distribution to be enforced through code rather than relying on centralized entities, thereby establishing trustless financial relationships between automated agents.

As these emerging technologies continue to mature, they will construct a new media economic model that fully captures the entire value creation chain from creators to platforms to users.

8. Using Blockchain as a Registration System for Intellectual Property and Traceability

Scott Duke Kominers: The emergence of generative AI has made it urgent to establish efficient, programmable mechanisms for registering and tracking intellectual property (IP) — aimed at ensuring the accuracy of traceability and supporting new business models arising from access, sharing, and derivative creation around IP. Existing IP frameworks rely on costly intermediaries and ex-post enforcement mechanisms, which are clearly inadequate in an era where AI can instantly consume content and generate variants with a single click.

What we need is an open, public registration system that provides creators with clear proof of ownership, is low in entry barriers, and highly efficient — while also allowing AI and other web applications to interact directly with it. Blockchain is well-suited to take on this role: it allows creators to register IP independently without relying on intermediaries and provides immutable proof of traceability; at the same time, it enables third-party applications to easily identify, authorize, and interact with these IP assets.

Of course, there remains caution regarding the overall concept of "can technology truly protect intellectual property." After all, the first two generations of the internet — and even the current AI revolution — are often associated with a decline in IP protection. One reason is that many existing IP business models emphasize "exclusion of derivative works" rather than incentivizing and monetizing derivative creations. Programmable IP infrastructure can not only allow creators, franchisees, and brands to clearly establish their IP ownership in the digital space but also foster new business models centered around "shared IP for generative AI and digital applications." In a sense, it transforms one of the threats posed by generative AI to creative work into new opportunities.

In the early stages of NFTs, we have already seen creators attempt to leverage new models, such as building brand network effects through CC0 on Ethereum to achieve value accumulation. Recently, we have seen infrastructure providers begin to construct standardized, composable IP registration and licensing protocols, even launching dedicated blockchains (like Story Protocol). Some artists have started using protocols like Alias, Neura, and Titles to license their styles and works to support creative remixing. Meanwhile, Incention's sci-fi series Emergence allows fans to participate in co-creating the universe and character settings, recording each creative contribution through the on-chain registration system on Story.

9. Web Crawlers That Can Compensate Content Creators

Carra Wu: The AI agents with the highest product-market fit today are not those used for programming or entertainment, but web crawlers — they can autonomously browse the internet, collect data, and make judgments about which links to follow.

According to some estimates, nearly half of today's internet traffic comes from non-human sources. Bots often ignore robots.txt files — which are supposed to inform automated crawlers whether they are allowed to access a site, but in reality, they have almost no binding power — and use the scraped data to reinforce the core moats of the world's largest tech companies. Worse still, websites ultimately have to bear the costs of these "uninvited guests," expending bandwidth and CPU resources to deal with the incessant flow of anonymous crawlers. In response, companies like Cloudflare and other CDNs (Content Delivery Networks) provide blocking services. All of this constitutes a "patchwork" system that should not exist.

We have previously pointed out that the original contract of the internet — content creators create content, and platforms are responsible for the economic coordination of content distribution — is gradually disintegrating. This trend is already reflected in the data: over the past twelve months, website operators have begun to massively block AI-targeted crawlers. In July 2024, only about 9% of the world's top 10,000 websites blocked AI crawlers, while that proportion has now risen to 37%. As more website operators mature in their technology and users become increasingly dissatisfied, this percentage will continue to rise.

So, what if we no longer pay CDNs to "one-size-fits-all" block suspected bots, but instead try a middle path? In other words, AI crawlers would no longer "free ride," but would pay for the right to access data. Here, blockchain can play a role: in this scenario, each web crawler agent holds a certain amount of cryptocurrency and negotiates on-chain with each website's "gatekeeper agents" or paywall protocols through the x402 protocol. (Of course, the challenge lies in robots.txt, the "robot exclusion standard," which has been deeply embedded in the operational models of internet companies since the 1990s. Changing this requires large-scale collaboration or support from CDNs like Cloudflare.)

Meanwhile, human users can prove their humanity through World ID (as mentioned earlier) to gain free access. In this way, content creators and website operators can receive compensation at the moment data is collected by AI, while human users can still enjoy an internet of freely flowing information.

10. Privacy-Protecting Advertising That Is Both Precise and Not "Creepy"

Matt Gleason: AI has begun to influence the way we shop online, but what if the ads we see every day could truly be "useful"? There are many reasons people dislike ads: irrelevant ads are pure noise; at the same time, not all "personalization" is a good thing. Highly targeted ads driven by vast amounts of consumer data can feel invasive; other applications attempt to monetize by "forcing ad views" (such as unskippable ads in streaming platforms or game levels).

Cryptographic technology can help improve these issues, providing an opportunity to reimagine the advertising system. When AI agents combine with blockchain, they can customize ads based on user-defined preferences, making ads neither irrelevant nor overly "creepy." More importantly, in this process, users' data will not be globally exposed, and users willing to share data or interact with ads can receive compensation.

To realize this model, several technical foundations are needed:

Low-Cost Digital Payment Systems: To compensate users for ad interactions (views, clicks, conversions), businesses need to send a large number of small payments. Achieving scalability requires the system to have high speed, high throughput, and nearly zero transaction fees.

Privacy-Preserving Data Verification: AI agents need to verify whether consumers meet certain demographic characteristics. Zero-Knowledge Proofs (ZKPs) can accomplish this verification without disclosing specific private information.

New Incentive Models: If the internet adopts a monetization model based on micro-payments (e.g., $0.05 per interaction), users can actively choose to view ads for compensation, thereby transforming the current "data extraction model" into a "user participation model."

For decades, people have been trying to make ads more "relevant" — online and offline alike. Reexamining advertising from the perspective of cryptographic technology and AI can truly make ads useful, controllable, and optional. For builders and advertisers, this means a more sustainable and consistent incentive structure; for users, it provides richer ways to discover information and explore the digital world.

Ultimately, this will not only make ad space more valuable but may also shake the deeply entrenched, "extractive" advertising economic model, replacing it with a more human-centered system: in which users are no longer "the product being sold," but true participants.

11. AI Partners "Owned and Controlled" by Users

Guy Wuollet: Nowadays, many people spend more time on devices than in offline interactions, and this online time is increasingly used to interact with AI models or AI-driven content. These models have already provided a form of "companionship" — whether for entertainment, information retrieval, satisfying niche interests, or as educational tools for children. It is easy to imagine that in the near future, AI partners aimed at education, healthcare, legal consulting, and even daily emotional companionship will become one of the primary modes of human interaction.

Future AI partners will be able to possess infinite patience and be deeply customized for individuals and their usage scenarios. They will not only be assistants or "robot servants" but may also become highly valued relational entities for users. Thus, the question arises: who truly owns and controls these relationships — the users, or the companies and other intermediaries? If you have ever been concerned about the content curation and moderation issues of social media over the past decade, this question will become exponentially more complex and personalized in the future.

The view that "anti-censorship hosting platforms like blockchain may be the best path to building uncensorable, user-controllable AI" has been thoroughly discussed. While users can run local models and purchase GPUs, for most people, this is either too costly or has too high a technical barrier.

Although there is still a distance to the widespread adoption of AI partners, the relevant technologies are rapidly maturing: text chat AI is already extremely natural and realistic; visual virtual avatars are also continuously improving; and blockchain performance is consistently enhancing. To make "uncensorable AI partners" truly user-friendly, we need to rely on better user experiences (UX) for cryptographic applications. Fortunately, wallets like Phantom have made blockchain interactions simpler, and technologies like embedded wallets, Passkey, and account abstraction allow users to easily achieve self-custody without having to manage mnemonic phrases. At the same time, high-throughput, trustless computing systems based on optimistic and ZK co-processors will enable us to establish meaningful and sustainable long-term relationships with digital partners.

In the near future, public discussions will shift from "when will realistic digital partners and virtual avatars appear" to "who will control them, and how will they be controlled."

免责声明：本文章仅代表作者个人观点，不代表本平台的立场和观点。本文章仅供信息分享，不构成对任何人的任何投资建议。用户与作者之间的任何争议，与本平台无关。如网页中刊载的文章或图片涉及侵权，请提供相关的权利证明和身份证明发送邮件到support@aicoin.com，本平台相关工作人员将会进行核查。