Web3Caff talks about decentralized AI agent infrastructure DeAgentAI: How to build a decentralized AI consensus mechanism and promote AI into the era of decentralized autonomy?

How will DeAgentAI specifically drive the governance of AI into a new era? This interview will provide an in-depth interpretation.

Author: Miki, Web3Caff Interview Team

Cover: Photo by Steve Johnson on Unsplash

DeAgentAI is actively exploring new approaches to AI governance by leveraging decentralized AI proxy infrastructure. Its core team is committed to solving the challenges faced by AI in terms of consensus, identity, and continuity, aiming to drive AI towards autonomous decision-making capabilities and achieve deep integration with the Web3 economic system. In this exclusive interview, DeAgentAI's co-founder Alex elaborated on how the integration of AI and Web3 can reshape the AI economy, and how the smart consensus mechanism can lead AI into a new era of decentralized autonomous governance. Currently, DeAgentAI has not only established a presence in the Movement, BTC, and BSC ecosystems, but also plans to expand its technology to areas such as smart cities, financial risk control, and medical AI, with the goal of endowing AI with identity on the blockchain and transforming it from an intelligent decision-making tool to a fully autonomous intelligent entity. So, how will DeAgentAI specifically drive the governance of AI into a new era? This interview will provide an in-depth interpretation.

1. First of all, thank you very much for DeAgentAI's participation in this exclusive interview column of Web3Caff. Please briefly introduce yourself, Web3Caff is a media platform dedicated to research in the Web3 field, and we welcome everyone to explore the development trends of the Web3 industry and new economic dynamics with us from a global perspective. First, could you please briefly introduce yourself, DeAgentAI, and your team?

Thank you very much for the invitation from Web3Caff. I am Alex, the co-founder of DeAgentAI. Although I initially worked in the fashion industry, technological innovation has always been a focus of my attention. At a technology salon, I witnessed the latest AIGC technology demonstration, where I saw AI create astonishing works of art in just a few seconds. This experience deeply impressed me and sparked my strong interest in AI technology, prompting me to start systematically learning and researching the AI field.

In the process of delving into AI, I had the privilege of meeting an AI expert focused on specialized domain translation models, Joe. Through in-depth discussions with him, I gradually realized that the integration of AI and Web3 would bring revolutionary changes, especially that the decentralized architecture might provide a completely new approach to solving the many challenges facing the development of AI. It was these ongoing discussions and reflections that allowed the concept of DeAgentAI to take shape, to build a "Decentralized AI Agent Infra", which is not only an innovation in technical infrastructure, but also a new exploration of the governance paradigm in the AGI era.

Speaking of the team composition, we have gathered a group of passionate professionals in the fields of AI and Web3. The core technical team mainly comes from top universities such as Carnegie Mellon University and UCLA, with rich experience in AI product development and Blockchain technology. At the same time, our operations team also has deep industry resources and a global vision, and this cross-domain professional background allows us to accurately grasp the trends of technological development and better understand and meet market demands.

2. DeAgentAI is committed to building a decentralized AI agent infrastructure and has proposed a breakthrough capability of AI AGENT to achieve consensus, consistency, and continuity in the decision-making layer. What do you think is the core mission of the team? While driving technological innovation, what broader impact does DeAgentAI hope to bring to the development of the Blockchain and AI industries?

Currently, the discourse power in the AI industry is still concentrated in the hands of private and centralized companies. As a team with faith in AI and Web3, we have a responsibility to find a new paradigm for the Web3 community to counter centralized AGI and ASI. Traditional decentralized communities rely on fixed and unchanging mathematical consensus and contract rules for governance, which often lack flexibility and cannot evolve with the development of the industry. We hope to solve the problems of consensus, consistency, and continuity through our new mechanism - the decentralized intelligent decision-making network, so that AI Agents have the ability of autonomous decision-making and execution, evolve to a higher form, and continuously co-build and co-exist with humans. New intelligent entities can evolve a flexible yet principled governance community.

The first-generation consensus mechanisms, such as PoW, PoS, or ZK, are based on pre-set mathematical algorithms and game strategies, so we are wondering if the next-generation consensus mechanism will be built on top of Agents with decision-making capabilities, hoping to usher in a new era of evolution from mechanical consensus to intelligent consensus by introducing AI Agents with decision-making capabilities into the governance process.

3. The concept of "a distributed processing framework that provides decision-making capabilities for AI Agents" is proposed. Compared to traditional AI agent infrastructure, how do you think this innovation breaks through industry pain points and provides unique value for application product implementation?

The core of this framework is to break through the limitations of traditional AI Agents, enabling AI to have true autonomous decision-making capabilities. Compared to traditional AI Agents, DeAgentAI, through its distributed architecture and intelligent consensus mechanism, allows AI to make decisions not only based on algorithmic models, but also by combining on-chain data, user feedback, and multi-party consensus, forming a more transparent and fair decision-making process. For example, in a decentralized second-hand trading market, when there is a dispute between the trading parties, the smart agent of DeAgentAI can act as an independent "judge" and make a relatively fair ruling based on smart contract rules, historical transaction data, and feedback from the consensus layer. This model reduces the impact of human emotional factors on decision-making and also reduces the possibility of malicious behavior, ensuring the credibility and stability of transactions.

4. Web3 provides a new paradigm for AI innovation, but this choice also comes with high complexity and uncertainty. What are the strategic considerations behind DeAgentAI's choice to focus on Web3 as the core scenario? How do you see the long-term value of Web3 in the future development of AI technology?

The choice to focus on Web3 as the core scenario is based on a deep understanding of the high degree of fit between the essence of AI and the underlying logic of Web3. In the traditional AI ecosystem, problems such as data monopoly, algorithmic black box, and unfair value distribution have long existed, while the decentralized architecture of Web3 and the return of data sovereignty to individuals provide a completely new paradigm for reconstructing the AI production relationship. To be precise, AI does not depend on the existence of Web3 to realize its functions, but for Web3 to truly achieve intelligence, autonomy, and large-scale collaboration, AI is an indispensable final piece of the puzzle.

We believe that the integration of Web3 and AI will trigger a "democratization of production tools" revolution, and its long-term value is reflected in these two dimensions: building an AI-native economic system and promoting an upgrade of the human-machine collaboration paradigm. The Tokenomics of Web3 will become the "circulatory system" for the flow of AI value. Behaviors such as data contribution, model optimization, and reasoning services can be automatically settled through smart contracts, forming a fine-grained and real-time feedback contribution measurement system.

Endowing AI agents with a true "digital identity" and "property rights". AI Agents can hold cryptocurrency wallets, autonomously pay Gas fees to execute on-chain operations, and even participate in business decisions through DAOs. This "AI as Participant" paradigm will give rise to hybrid collaboration forms of human-AI-organization, such as the "AI on-chain fund" that DeAgentAI is exploring.

5. As the project with the largest user base and most frequent on-chain interactions in the Movement, BTC, and BSC ecosystems, DeAgentAI plays an important role in these ecosystems. How do you see DeAgentAI's positioning in these three ecosystems? Do you have any plans to launch new functions or services in these ecosystems in the future to further consolidate and expand your market share?

DeAgentAI is not only a key builder of the technical infrastructure in the Movement, BTC, and BSC ecosystems, but also the core engine driving the popularization of decentralized AI Agents. We want to build a seamlessly collaborative smart framework that can work across chains, ensuring that users can enjoy a consistent and efficient experience in different ecosystems.

In the future, we will further expand the ecosystem boundaries of DeAgentAI, integrating more on-chain applications and scenarios to enhance the adaptability and scalability of AI Agents in cross-chain environments. We will also invite global developers to participate in the open-source framework of DeAgentAI, jointly promoting the ecosystem co-construction of decentralized AI technology.

6. DeAgentAI emphasizes improving model performance through user behavior data. How to achieve a positive feedback loop between "user participation-driven technology optimization" and "technology service-driven user value"? Do you plan to further incorporate users into the deeper decision-making chain of the model in the future?

One of the core ideas of DeAgentAI is to build a user-centric technology ecosystem, continuously optimizing model performance through user behavior data. But this is not just about technological progress, but also an extension of user value. We hope to establish a continuous positive feedback loop between "user participation-driven technology optimization" and "technology service-driven user value", so that the two can promote each other and form a closed loop.

The key to achieving this loop is data-driven optimization, user experience enhancement, and transparent co-creation mechanisms. User interaction data is an important basis for model evolution, and we will extract optimization directions from user needs and feedback, quickly iterate product functions, and the optimized technology will in turn create higher value for users, further enhancing their participation and trust, thereby driving more data feedback. In addition, through the unique consensus mechanism of DeAgent, users not only can see the process of technological progress, but also can truly feel their own contributions, enhancing their sense of belonging and collaboration motivation.

In the future, we hope to further deepen the role of users in the model decision-making chain, allowing them not only to be data providers, but also to actively participate in the co-creation of the AI ecosystem. We plan to introduce an open training mechanism to encourage users with technical capabilities to contribute datasets or optimize algorithms, thereby enhancing the adaptability of the models. At the same time, we are also exploring the combination of decentralized governance, allowing some model parameters or behavioral strategies to be determined by user voting or smart contracts, ensuring that the development direction of AI is consistent with real needs.

The core goal of all this is to promote the deep integration of AI technology and user needs, making DeAgentAI not only a diverse intelligent agent, but also a decentralized AI ecosystem that can grow together with users.

7. Does DeAgentAI have plans to expand into more diversified fields, such as smart cities, financial risk control, or medical AI? In the future, what kind of benchmark do you hope DeAgentAI will become in the industry?

DeAgentAI has always focused on the deep application of AI technology in different fields, such as the three scenarios mentioned above: smart cities, financial risk control, and medical AI. In the field of smart cities, AI Agents can optimize governance data analysis and resource allocation to improve the efficiency of urban operations and make more accurate decisions. In the field of financial risk control, they can provide real-time and accurate risk assessment and credit management support, bringing more efficient risk control models to decentralized finance (DeFi) and traditional financial institutions. In the field of medical AI, AI can assist doctors in auxiliary diagnosis, personalized treatment plan recommendations, and intelligent allocation of medical resources.

These areas are highly aligned with the core capabilities of DeAgentAI in terms of "consensus, identity and continuity". We hope that DeAgentAI will not only be a technology provider, but also a shaper of the future AI governance paradigm, by building a user-trusted AI application standard and an AI ecosystem where technology and trust coexist, through an open and transparent distributed governance mechanism. The vision of DeAgentAI is to become a "new social infrastructure", leading the next-generation AI governance framework and promoting the deep integration of technology and human values, while empowering the industry.

8. New competitors are constantly emerging in the current AI and Block Chain fields. What trends do you foresee in the integration of these two fields in the next 3 to 5 years? How will the DeAgentAI team ensure that it maintains a leading advantage in this highly competitive market?

The deep integration of AI and Block Chain is an important trend in the next 3 to 5 years. We foresee more scenarios where "on-chain intelligent agents" and "off-chain large models" will work collaboratively, and decentralized AI will no longer be a simple combination of data certification or model invocation, but will develop into truly autonomous intelligent systems with on-chain decision-making capabilities and incentive mechanisms. The leading advantage of DeAgentAI lies in the fact that we have been focused on building this new paradigm from the very beginning: our models not only have strong decision-making capabilities, but also ensure their credibility and transparency through consensus mechanisms and verification systems. To maintain competitiveness, we will continue to invest in technology R&D, optimize model performance, and deepen ecosystem cooperation to expand the application scenarios of DeAgentAI in different chains and vertical fields.

9. In the team's view, what is the most challenging goal for DeAgentAI in the future? In which areas will the team invest more resources and efforts to achieve these goals? Faced with the rapid changes in technology, market and user needs, how do you ensure that the team always maintains agility and innovation?

The biggest challenge facing DeAgentAI is to establish a standardized system of decentralized AI Agents globally. This is not only a technical challenge, but also involves governance models, user habits, and the coordination of cross-chain ecosystems. To this end, we will increase our R&D investment in model interpretability, cross-chain compatibility, and smart contract security. In addition, we also attach great importance to community building and the expansion of ecosystem partnerships, ensuring that our products always meet market demands by introducing diverse developers and user feedback. Within the team, we implement agile development and rapid iteration mechanisms, and encourage cross-disciplinary innovative collaboration to maintain the forefront of technology and ideas. We believe that only by establishing a strong symbiotic relationship between technology, products, and community can DeAgentAI maintain a leading position in the ever-changing Web3 and AI fields.

10. Finally, I would like to express my sincere gratitude to DeAgentAI for participating in this interview. Today's discussion is of great significance, allowing us to gain a deeper understanding of DeAgentAI and providing valuable insights for friends who are interested in AI innovation projects. I'm sure there have been many unforgettable moments in the development of DeAgentAI. Could you share with us some unexpected inspirations or interesting anecdotes that occurred during the project's advancement or in the team's collaboration?

Haha, this reminds me of a story about myself. Even when the price of BTC was only a few thousand dollars, I had already started paying attention to it. At that time, I happened to have some money in hand, and my friend and I sat down and discussed for an afternoon, whether to use the money to buy BTC or to buy the camera I had been longing for. We weighed the pros and cons repeatedly, and finally decided to go out for dinner first, and then make the final decision when we came back. And the result? We went out, had dinner, and then... bought the camera :)

Although I missed out on BTC at the time, this experience has made me more deeply understand the concept of opportunity cost, and even influenced my subsequent decision-making. Perhaps it is these "should have bought BTC" experiences that have filled me with enthusiasm for the development of decentralized technology.

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