Original author: NingNing (X: @0x Ning 0x )
Regarding the prospects of AI+Crypto, there are very different views in the industry, forming a fierce three-way debate:
Optimists: The decentralized revolution of AI
AI+Crypto optimists firmly believe that blockchain technology can and should revolutionize the way AI is developed and applied. Their vision includes:
1. Decentralized AI: Break the monopoly of large technology companies on AI and create an open AI ecosystem in which everyone can participate.
2. ZKML (Zero-Knowledge Machine Learning): Use 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 original data.
3. Data sovereignty: Through blockchain technology, users can truly own and control their own data, and at the same time gain economic rewards from the use of their data by AI systems.
4. Trustless collaboration: Use smart contracts to coordinate AI researchers and developers around the world without the need for a centralized management agency. In the eyes of optimists, AI+Crypto is not only a combination of technologies, but also a revolution in democratizing AI, which has the potential to completely change the development trajectory of AI.
Pessimistic: Vitalik’s Caution
In contrast, Ethereum founder Vitalik Buterin represents a more cautious attitude. He believes that in the next 10 years, the application scenarios of AI+Crypto should be actively limited to several specific areas:
1.DEX AI Bot Market Maker
2. Prediction Market Maker
3. DAO Automated Governance
Vitaliks view represents a minimalist approach that attempts to limit AI+Crypto to a relatively narrow but controllable range. The considerations behind this view 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: Finding a Balance
Between the optimists and pessimists, some realists are exploring more pragmatic solutions. They recognize the potential of AI+Crypto, but also realize the huge challenges of achieving fully decentralized AI. These realists are trying:
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 the traditional AI and blockchain worlds instead of completely overthrowing the existing system.
In this heated debate, a striking project has emerged: KIP Protocol. It seems to be trying to find a delicate balance between ideals and reality, absorbing some of the visions of optimists, maintaining the caution of pessimists, and at the same time not losing the pragmatic attitude of realists.
So, how does KIP Protocol position itself? Can it become a key link connecting the worlds of AI and Crypto? Let’s take a deep look at 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 each AI-related knowledge asset (dataset, model, application).
This approach not only responds to Vitaliks focus on clear 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, KIPs approach is fundamentally different:
- Coze/Dify model: User-generated content and data belong to the platform.
- KIP model: 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 stake in the AI economy. This shift could redefine the fundamental rules of the digital economy.
2. Decentralized value distribution: from tenant farmers to shareholders
The settlement layer of KIP Protocol builds a transparent and automated profit distribution system through smart contracts and $KIP tokens. This mechanism is similar to the DEX AI Bot market maker proposed by Vitalik: both attempt 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 a specific application scenario, but an attempt to create a new value distribution model for the entire AI industry chain. Here, we see a sharp contrast with traditional AI platforms:
- Coze/Dify model: The platform obtains most of the revenue, and developers are compensated through limited sharing. - KIP model: The smart contract automatically and transparently distributes the revenue, and all participants can get the corresponding share according to their contribution.
This model could spur more innovation because it provides a platform for smaller players to compete with larger companies.
3. Open AI infrastructure: Beyond a single application
The application layer of KIP Protocol provides a standardized API interface, allowing any AI component (data, model, application) to seamlessly integrate into this open ecosystem.
This open architecture contrasts sharply with the closed ecosystems of traditional AI platforms:
- Coze/Dify model: Building a closed ecosystem around the platform, with the risk of vendor lock-in.
- KIP Model: Create an open AI asset market to encourage cross-platform and cross-domain collaboration and innovation.
By creating an open, composable AI infrastructure, KIP not only lowers the threshold for innovation, but also creates possibilities for cross-domain collaboration.
4. Practical application scenarios of KIP Protocol
To better understand how KIP Protocol works in practice, let’s look at a few specific application scenarios:
a) Decentralized medical data sharing
Imagine a doctor studying a rare disease who needs a large amount of patient data to train an AI model. Traditionally, this may 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 $KIP tokens to access this data.
- Smart contracts automatically execute revenue distribution, and patients are paid for contributing their data.
- ZKML technology ensures data privacy while allowing model training and validation.
This not only accelerates medical research, but also creates new revenue streams for patients while protecting privacy.
b) Decentralized AI creation market
Consider an AI-assisted creation scenario:
- Writers, artists, and musicians can upload their works as intellectual assets to the KIP ecosystem.
- AI developers can use these assets to train domain-specific authoring models.
- Users can use these models to assist in their creations, and each use will automatically distribute the proceeds to the original creators and model developers through smart contracts.
This creates a fair creative ecosystem where every participant benefits.
c) Enterprise-level knowledge management
Large enterprises can leverage KIP Protocol to better manage and monetize their internal knowledge:
- Transform the companys various documents, reports and data into knowledge assets.
- Employees can retrieve and use these assets more easily, improving work efficiency.
- Companies can choose to open up some non-sensitive knowledge assets to the outside world and create new revenue streams. This not only improves 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 momentum, KIP Protocols model is also fundamentally different from traditional platforms:
- Coze/Dify model: Innovation is mainly determined and driven by the platform, and developers need to adapt to the rules and restrictions of the platform.
- KIP model: 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 innovations, while the tokenization model may breed more unexpected and disruptive innovations.
6. Realistic business model
Although KIP Protocol has a grand vision, its pragmatic attitude is worth noting:
- Completed US$10 million in financing, with investors including well-known institutions.
- It has actual customers and revenue, and does not rely on token issuance to raise money.
- Collaboration with Open Campus in the field of Web3 education shows its potential in practical application scenarios.
- Development is not limited to Web3. Web2 also has partners, and the business landscape of Web2 and Web3 is advancing in parallel
This down-to-earth approach may be the antidote to the 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 a business model that can create real value.
7. Challenges and thoughts
Despite this, KIP Protocol still faces many challenges:
- Technical complexity: Although KIP Protocol aims to simplify the management of AI assets, it may still be difficult for ordinary users to understand and use the system.
- Ecosystem construction: To truly form a network effect, KIP Protocol needs to attract enough high-quality participants, which is a long process.
- Competition with existing giants: It is not easy to change the established industry landscape, and KIP Protocol needs to demonstrate overwhelming advantages.
In addition, KIP will also need to compete with traditional AI platforms in terms of user experience. Platforms such as Coze and Dify may be more likely to gain widespread adoption in the short term due to their user-friendly interfaces. How KIP can provide the same smooth user experience while maintaining the advantages of decentralization will be a key challenge.
Conclusion: Finding a balance between ideals and reality
KIP Protocols attempt represents a possible path for the integration of AI and Crypto. It is neither as conservative as Vitalik suggested, limiting AI and Crypto to a few specific scenarios; nor is it like some radical projects that try to decentralize the three elements of AI: data, computing power, and models. On the contrary, KIP chose a middle path: using blockchain technology to reconstruct the value distribution mechanism of the AI industry chain.
Whether this approach will be successful remains to be tested by time. But it at least provides us with a framework for thinking: the future of AI+Crypto may not lie in creating 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 between tokenized models like KIP and traditional AI platforms. Some users may choose convenient centralized platforms, while others, especially those who value data ownership and economic returns more, may turn to tokenized solutions.
For investors and industry observers, KIP Protocol represents an experiment worth watching. It may not deliver 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.
