Original Author: NingNing (X: @0xNing0x)

Regarding the prospects of AI+Crypto, there are sharply contrasting views within the industry, leading to an intense three-way debate:

Optimists: The Decentralized Revolution of AI

Optimists of AI+Crypto firmly believe that blockchain technology can and should fundamentally change the way AI is developed and applied. Their vision includes:

1. Decentralized AI: Breaking the monopoly of large tech companies on AI and creating an open AI ecosystem that everyone can participate in.

2. ZKML (Zero-Knowledge Machine Learning): Utilizing zero-knowledge proof technology to train and verify AI models, ensuring the privacy, verifiability, and integrity of AI. This means we can prove the correctness and fairness of AI models without exposing the raw data.

3. Data Sovereignty: Allowing users to truly own and control their data through blockchain technology, while also gaining economic returns from AI systems that use their data.

4. Trustless Collaboration: Using smart contracts to coordinate AI researchers and developers globally without the need for centralized management. To optimists, AI+Crypto is not just a combination of technologies but a revolution in democratizing AI, with the potential to completely change the trajectory of AI development.

Pessimists: Vitalik's Cautionary Perspective

In contrast, Ethereum founder Vitalik Buterin represents a more cautious attitude. He believes that in the next decade, the application scenarios of AI+Crypto should be actively limited to a few specific areas:

1. DEX AI Bot Market Makers

2. Prediction Market Makers

3. DAO Automated Governance

Vitalik's viewpoint represents a "minimalist" approach, attempting to confine AI+Crypto to a relatively narrow but controllable scope. The considerations behind this perspective may include concerns about the potential risks of AI, an understanding of the current limitations of blockchain technology, and vigilance against the proliferation of speculative projects.

Realists: Seeking a Balance

Between the optimists and pessimists, some "realists" are exploring more pragmatic solutions. They recognize the potential of AI+Crypto but also acknowledge the significant challenges in achieving fully decentralized AI. These realists are attempting to:

1. Tokenize AI models, knowledge bases, and AI agents to create new value capture models.

2. Explore the application of new technologies like ZKML in specific scenarios rather than pursuing a comprehensive technological revolution.

3. Build bridges connecting the traditional AI and blockchain worlds instead of completely overturning existing systems.

In this intense debate, a noteworthy project has emerged: KIP Protocol. It seems to be trying to find a subtle balance between ideals and reality, absorbing some visions of the optimists while maintaining the caution of the pessimists, all without losing the pragmatic attitude of the realists.

So, how does KIP Protocol position itself? Can it become a key link connecting the worlds of AI and Crypto? Let’s delve into this ambitious project:

1. Redefining AI Assets: From Data to Equity

The core innovation of KIP Protocol lies in its "Ownership Layer." Through the ERC-3525 semi-fungible token (SFT) standard, KIP provides clear on-chain ownership proof for every AI-related knowledge asset (datasets, models, applications).

This approach addresses Vitalik's concerns about clear value capture while expanding the boundaries of tokenization. It is not merely about converting AI assets into tokens but creating a new concept of "digital equity."

Compared to traditional AI agent platforms (like Coze and Dify), KIP's approach is fundamentally different:

• Coze/Dify Model: User-generated content and data are owned by the platform.

• KIP Model: Users retain ownership of the content and data they create.

Imagine your data no longer being passively collected by large companies but becoming your shares in the AI economy. This shift could redefine the fundamental rules of the digital economy.

2. Decentralized Value Distribution: From "Tenants" to "Shareholders"

KIP Protocol's "Settlement Layer" builds a transparent, automated revenue distribution system through smart contracts and the $KIP token. This mechanism is akin to what Vitalik proposed for DEX AI Bot market makers: both aim to achieve fairer and more efficient value distribution through algorithms and smart contracts.

But KIP goes further. It is not just a mechanism designed for specific application scenarios; it seeks to create a new value distribution model for the entire AI industry chain. Here, we again see a stark contrast with traditional AI platforms:

• Coze/Dify Model: The platform captures the vast majority of revenue, and developers receive compensation through limited sharing.

• KIP Model: Smart contracts automatically and transparently distribute revenue, allowing all participants to receive corresponding shares based on their contributions.

This model could stimulate more innovation, as it provides smaller participants with a platform to compete with large companies.

3. Open AI Infrastructure: Beyond Single Applications

KIP Protocol's "Application Layer" offers standardized API interfaces, allowing any AI component (data, models, applications) to seamlessly integrate into this open ecosystem.

This open architecture sharply contrasts with the closed ecosystems of traditional AI platforms:

• Coze/Dify Model: Builds a closed ecosystem around the platform, posing a "vendor lock-in" risk.

• KIP Model: Creates an open AI asset market that encourages cross-platform and cross-domain collaboration and innovation.

By establishing an open, composable AI infrastructure, KIP not only lowers the barriers to innovation but also creates possibilities for cross-domain collaboration.

4. Practical Application Scenarios of KIP Protocol

To better understand how KIP Protocol operates in practice, let’s look at a few specific application scenarios:

a) Decentralized Medical Data Sharing

Imagine a doctor researching rare diseases needing a large amount of patient data to train an AI model. Traditionally, this might involve complex data-sharing agreements and privacy issues. With KIP Protocol:

• Patients can upload their anonymized medical data as knowledge assets and set access conditions.

• Researchers can pay with $KIP tokens to access this data.

• Smart contracts automatically execute revenue distribution, rewarding patients for contributing data.

• ZKML technology ensures data privacy while allowing model training and verification.

This not only accelerates medical research but also creates new income sources for patients while protecting privacy.

b) Decentralized AI Creation Market

Consider a scenario of AI-assisted creation:

• Writers, artists, and musicians can upload their works as knowledge assets to the KIP ecosystem.

• AI developers can use these assets to train creation models in specific fields.

• Users can utilize these models to assist in creation, with each use automatically distributing revenue to the original creators and model developers through smart contracts.

This creates a fair creative ecosystem where every participant can benefit.

c) Enterprise Knowledge Management

Large enterprises can leverage KIP Protocol to better manage and monetize their internal knowledge:

• Transform various company documents, reports, and data into knowledge assets.

• Employees can more easily retrieve and use these assets, improving work efficiency.

• Companies can choose to open some non-sensitive knowledge assets to the public, creating new revenue streams. This not only enhances the efficiency of knowledge management but also opens up new profit models for companies.

5. Innovation Incentives: Top-Down vs. Bottom-Up

In terms of innovation dynamics, KIP Protocol's model also fundamentally differs from traditional platforms:

• Coze/Dify Model: Innovation is primarily determined and driven by the platform, and developers must adapt to the platform's rules and limitations.

• KIP Model: Innovation can come from any participant in the ecosystem, allowing developers to freely combine and innovate.

This difference could lead to two completely different innovation ecosystems. Traditional platforms may find it easier to achieve short-term, directed innovations, while the tokenization model may foster more unexpected, disruptive innovations.

6. Realistic Business Model

Despite KIP Protocol's grand vision, its pragmatic attitude is noteworthy:

• Completed $10 million in funding, with investors including well-known institutions.

• Has actual customers and revenue, not relying on token issuance for "fundraising."

• Collaboration with Open Campus in the Web3 education sector demonstrates its potential in practical application scenarios.

• Development is not limited to Web3. There are also partners in Web2, advancing the business landscape of both Web2 and Web3 simultaneously.

This down-to-earth approach may be the antidote to the speculative projects that Vitalik is concerned about. At the same time, it proves that the tokenization model is not just a castle in the air but a business model that can create actual value.

7. Challenges and Reflections

Nevertheless, KIP Protocol still faces numerous challenges:

• Technical Complexity: Although KIP Protocol aims to simplify the management of AI assets, understanding and using this system may still be difficult for ordinary users.

• Ecosystem Building: To truly form network effects, KIP Protocol needs to attract a sufficient number of quality participants, which is a lengthy process.

• Competition with Existing Giants: Changing an already established industry landscape is no easy task, and KIP Protocol needs to demonstrate overwhelming advantages.

Additionally, KIP must compete with traditional AI platforms in terms of user experience. Platforms like Coze and Dify, with their user-friendly interfaces, may find it easier to gain widespread adoption in the short term. How KIP can provide a similarly smooth user experience while maintaining its decentralized advantages will be a key challenge.

Conclusion: Finding Balance Between Ideals and Reality

KIP Protocol's attempt represents a possible path for the integration of AI+Crypto. It is neither as conservative as Vitalik suggests, limiting AI+Crypto to a few specific scenarios, nor as radical as some projects that attempt to decentralize all three elements of AI: data, computing power, and models. Instead, KIP has chosen a middle path: reconstructing the value distribution mechanism of the AI industry chain using blockchain technology.

Whether this approach will succeed remains to be seen. However, it at least provides us with a framework for thinking: the future of AI+Crypto may not lie in creating entirely new application scenarios but in how to use blockchain technology to transform the existing AI industry chain to make it more open, fair, and efficient.

In the future, we may see the coexistence and competition of tokenization models like KIP with traditional AI platforms. Some users may choose convenient centralized platforms, while others, especially those who value data ownership and economic returns, may turn to tokenized solutions.

For investors and industry observers, KIP Protocol represents an experiment worth watching. It may not bring explosive short-term returns like some Memecoins, but it has the potential to reshape the infrastructure of the entire AI industry in the long run.

Original Link

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。