AI Asset Tokenization: KIP Protocol's AI+Crypto Realism Route

Original author: NingNing (X: @0x Ning 0x)

There are radically different views within the industry on the prospects of AI+Crypto, leading to a heated three-party debate:

Optimists: The Decentralization Revolution of AI

Optimists of AI+Crypto believe that blockchain technology can and should fundamentally change the development and application of AI. Their vision includes:

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

2. ZKML (Zero-Knowledge Machine Learning): Using Zero-Knowledge Proof technology to train and verify AI models, ensuring the privacy, verifiability, and integrity of AI. This means that we can prove the correctness and fairness of AI models without exposing the original data.

3. Data Sovereignty: Through blockchain technology, users truly own and control their own data, while being able to gain economic returns from AI systems using their data.

4. Decentralized collaboration: Use smart contracts to coordinate AI researchers and developers worldwide without the need for centralized management institutions.

In the view of optimists, AI+Crypto is not only a combination of technologies, but also a revolution in democratizing AI, with the potential to completely change the trajectory of AI development.

Pessimist: Vitalik’s Prudent Theory

On the contrary, Ethereum founder Vitalik Buterin represents a more cautious attitude. He believes that in the next 10 years, the application scenarios of AI+Crypto should proactively be limited to several specific areas:

1. DEX AI Bot Market Maker

2. Prediction market maker

3. DAO Automated Governance

Vitalik’s views represent a ‘minimalist’ approach, attempting to confine AI+Crypto within a relatively narrow but controllable scope. The considerations behind this viewpoint may include concerns about the potential risks of AI, awareness of the current limitations of blockchain technology, and vigilance against the proliferation of speculative projects.

Realists: Seeking a Balance

Between optimists and pessimists, some ‘realists’ are exploring more practical solutions. They recognize the potential of AI+Crypto but also realize the enormous challenges facing the realization of comprehensive Decentralization AI. These realists are attempting:

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

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

3. Build a bridge between traditional AI and the blockchain world, rather than completely overturning existing systems.

In this intense debate, one notable project emerged: KIP Protocol. It seems to be trying to find a delicate balance between idealism and reality, absorbing some of the optimistic visions of the optimists while maintaining the caution of the pessimists, all while not losing the pragmatism of the realists.

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

1. Redefining AI Assets: From Data to Equity

The core innovation of the 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 (dataset, model, application).

This method not only responds to Vitalik’s follow on explicit value capture, but also expands the boundaries of tokenization. It is not just a simple conversion of AI assets into tokens, but creates a new concept of ‘digital equity’.

Compared with traditional AI Agent platforms such as Coze and Dify, KIP’s approach has fundamental differences:

• Coze/Dify mode: The content and data created by users belong to the platform.

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

Imagine that your data is no longer passively collected by big companies, but becomes your share in the AI economy. This shift could potentially redefine the fundamental rules of the digital economy.

2. Value distribution of Decentralization: From ‘tenant farmers’ to ‘shareholders’

The ‘Settlement Layer’ of the KIP Protocol has built a transparent, automated profit distribution system through Smart Contracts and $KIP Token. This mechanism is similar to Vitalik’s proposal for DEX AI Bot market makers: both are trying to achieve fairer and more efficient value distribution through Algorithm and Smart Contract.

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

• Coze/Dify mode: the platform obtains the majority of the profits, and developers receive rewards through limited profit sharing.
• KIP mode: Smart Contracts automatically and transparently distribute profits, and all participants can receive corresponding shares based on their contributions.

This model may stimulate more innovation as it provides a platform for small participants to compete with large companies.

3. Open AI Infrastructure: Beyond Single Applications

The ‘Application Layer’ of the KIP Protocol provides standardized API interfaces, allowing any AI component (data, model, application) to seamlessly integrate into this open ecosystem.

This open architecture forms a stark contrast to the closed ecosystem of traditional AI platforms:

• Coze/Dify mode: Building a closed ecosystem around the platform, with the risk of ‘vendor lock-in’.

• KIP Mode: Create an open AI asset market to encourage cross-platform, cross-domain collaboration and innovation.

By creating an open and composable AI infrastructure, KIP not only drops the innovation barrier, but also creates possibilities for cross-domain collaboration.

4. Actual Application Scenarios of KIP Protocol

To better understand how KIP Protocol operates in practice, let’s take a look at several specific use cases:

a) Decentralization medical data sharing

Imagine a doctor who studies rare diseases needing a large amount of patient data to train AI models. In traditional methods, this may involve complex data sharing protocols and privacy issues. But with KIP Protocol:

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

• Researchers can pay $KIP Token to access this data.

• Smart contracts automatically execute profit distribution, and patients receive rewards for contributing data.

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

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

b) Decentralization AI Creation Market

Consider a scenario of AI-assisted creation:

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

• AI developers can use these assets to train models for specific domains of creation.

• Users can use these models to assist in creation, and each use will automatically allocate profits to the original creator and model developer through Smart Contract.

This creates a fair creative ecosystem from which every participant can benefit.

c) Enterprise Knowledge Management

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

• Convert various documents, reports, and data of the company into knowledge assets.

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

• Companies can choose to open up some non-sensitive intellectual assets to the outside world to create new revenue streams.

This not only improves the efficiency of knowledge management, but also opens up new profit models for the company.

5. Innovative Incentives: Top-down vs. Bottom-up

In terms of innovation power, the KIP Protocol model also has fundamental differences from traditional platforms:

• Coze/Dify mode: Innovation is mainly determined and driven by the platform, and developers need to adapt to the platform’s rules and limitations.

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

This difference may lead to two completely different innovation ecosystems. Traditional platforms may be more likely to achieve short-term, directional innovation; while the tokenization model may give birth to more unexpected and disruptive innovation.

6. Realistic Business Model

Despite the grand vision of KIP Protocol, its pragmatic attitude is worth following:

• Raised $10 million in funding, with investments from well-known institutions.

• With real customers and revenue, not relying on Token issuance" fundraising".

• The cooperation with Open Campus in the Web3 education field demonstrates its potential in practical application scenarios.

• Development is not limited to Web3. Web2 also has partners, and the commercial landscape of Web2 and Web3 is advancing side by side.

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

7. Challenge and Thinking

However, KIP Protocol still faces many challenges:

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

• Ecological construction: To truly form a network effect, KIP Protocol needs to attract a sufficient number of high-quality participants, and this is a long process.

• Competition with existing giants: it is not easy to change the established industry pattern, KIP Protocol needs to demonstrate overwhelming advantages.

In addition, KIP also needs to compete with traditional AI platforms in terms of user experience. Platforms like Coze and Dify, with their user-friendly interfaces, may be more easily adopted in the short term. How KIP provides the same smooth user experience while maintaining the advantage of Decentralization will be a key challenge.

Conclusion: Finding a Balance Between Ideal and Reality

The attempt of KIP Protocol represents a possible path for the fusion of AI+Crypto. It is neither as conservative as Vitalik’s suggestion, limiting AI+Crypto to a few specific scenarios, nor as radical as some ambitious projects attempting 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 with blockchain technology.

Whether this method can succeed remains to be tested over time. But it at least provides us with a thinking framework: the future of AI+Crypto may not lie in creating completely new application scenarios, but in how to transform the existing AI industry chain with blockchain technology, making 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 tokenization solutions.

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

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