This article is translated from Sonny Young's in-depth industry analysis article "Why will AI agents become the next hot narrative of Web3?" published on Medium. 》, with slight deletions that do not affect willingness. This article starts from the function of AI agent, analyzes the advantages and development direction of AI agent, and introduces its wide range of applications in Web3.0. Come and take a look with Xiaowan!

What is an AI agent?

Imagine you build a game like Mario Kart. As an AI agent in the game, Mario has a significant impact on the outcome of the game. He'll need to make decisions throughout the game, such as when to accelerate, turn, and jump, in order to deftly avoid obstacles, overtake other racers, and ultimately win the race. In this example, the entire game environment and the actions of other racers make up the AI ​​agent's environment. AI agents make optimal decisions based on this information. For example, if the road ahead turns left, the agent will turn left.

The essence of an AI agent is a system that can perceive its environment, make decisions and take actions based on given goals. These decisions are based on the AI ​​agent’s understanding of the environment, such as its destination, current location, and surrounding obstacles. One of the most impressive properties of AI agents is their adaptability. It is able to "learn," meaning it can continuously improve its decision-making process through interaction with its environment. For example, after multiple games, it might learn how to better avoid obstacles or find the best racing route, demonstrating its ability to evolve and adapt.

To sum up, an AI agent is an AI system that can perceive and understand its environment, make decisions, take actions, and continuously learn and evolve.

AI agent - the next hot topic

In the development process of large-scale language models, the next evolution will proceed in two directions. On the one hand, it goes "downward" and focuses on updating and improving the underlying system. On the other hand, it is "upward" expansion, which enhances productivity from a higher dimension by increasing complexity, intelligence and automation levels - this is essentially the development of the agent model. A typical agent module unit integrates multiple components such as memory, planning, execution, and reflection, making it more intelligent than the traditional large-scale language model interaction model.

Not only that, people continue to add features to these systems in order to meet various needs.Add exciting new features to continuously expand the boundaries of imagination. Some outstanding innovative ideas, such as integrated search engine and compiler functions, have been gradually realized in recent months of research.

While single agents are powerful and easy to use, OpenAI GPTs represent the future of independent agent-based AI business models. In this model, developers and users work together to create, customize and purchase GPTs that meet their needs. OpenAI then shares the resulting profits with developers. This collaborative business model not only promotes community cohesion, but also closely connects the community, developers, platforms and users to jointly move towards the grand vision of AI progress.

However, our vision should never be limited by current possibilities. The future of AI is vast, and our imaginations should stretch with it. The potential for AI evolution is huge, and this endless potential can inspire us and ignite our enthusiasm. For example, can agents within GPTs have the ability to learn and evolve independently?

Challenges of AI in Web3

In short, the core challenge of Web3 is that there are no projects that are truly tailored for users. The “users” here refer to the broad group of people who do not have knowledge of complex trading strategies, are not familiar with Rust language programming, and do not know how to obtain accurate data from platforms such as Massari, Dune or DeBank. In the infancy of Web3, these users are particularly critical because they constitute the broadest user base in the field and must be effectively attracted and retained.

Web2 migration

The smooth transition of Web2 users to Web3 has far-reaching significance in many aspects. First of all, Web3 marks the advent of the decentralized era, giving users unprecedented control over their data, identity, and digital assets. By migrating Web2 users to Web3, we are not only democratizing technology, but also strengthening the sovereignty of users, allowing them to truly own and manage their online identity and data circulation. This shift responds to public concerns about data privacy, censorship, and surveillance in centralized platforms, providing users with a new choice centered on transparency, security, and empowerment.

Secondly, the introduction of Web2 users is crucial to promoting the widespread application and mainstream acceptance of Web3. Web3 is not limited to the financial field. It has the potential to revolutionize many fields such as healthcare, supply chain management, voting systems, and content creation.. With the addition of Web2 users, we will further expand the user base and ecosystem of decentralized applications. This network effect will accelerate the development and maturity of decentralized networks. This widespread adoption not only verifies the practical value and vitality of Web3, but will also inspire more investment, research, and innovation in decentralized technology to build a more robust, inclusive, and dynamic digital future.

Large-scale adoption and market transformation

In today's market landscape, many teams are quietly investing in the development of AI agent projects in the Web3 field. As competition in this space intensifies, a forward-looking strategic vision becomes critical to navigating this turbulent market. Clearly, in this environment, the core of efficiency lies in precise market transformation, focusing on cultivating a unique and outstanding AI agent project, rather than spreading resources to try to become a comprehensive center for multiple AI projects.

This approach deeply recognizes the complexity and multifaceted nature of the competitive environment, where differentiation and innovation are prerequisites for achieving market leadership. By focusing resources and efforts on developing a best-in-class AI agent program, enterprises can stay ahead of this evolving Web3 revolution. Furthermore, this strategy is not limited to meeting the needs of the Web3 community, but has an ambitious vision to transform and serve Web2 users around the world.

By adopting this comprehensive and forward-looking strategy, companies can capture market share in the emerging Web3 ecosystem and promote seamless integration and adoption by global audiences. Centralized technology. This will establish the company as an industry leader in the transformative digital field and ensure its continued prosperity in this market full of opportunities and challenges.

Endless possibilities

Combining AI agents with Web3 technology not only creates powerful synergies, but also greatly enhances decentralized applications (dApps) functions, improve user experience and drive innovation. The following are the specific ways in which AI agents are integrated with Web3 technology and the benefits they bring:

01 Decentralized Self-Organizations (DAOs)

Intelligent decision support: AI agents provide key insights to DAOs through in-depth analysis of data, helping them make more informed and efficient decisions.

Automated governance process: AIDelegates automate the governance process including voting and proposal evaluation, allowing DAOs to respond to various situations more quickly and efficiently.

02 Smart Contract

Advanced automation capabilities: AI agents can act on complex conditions and data Input triggers and manages smart contracts to automate more complex and sophisticated processes.

Predictive analysis and optimization: Using advanced machine learning models, AI agents can predict contract execution results, thereby optimizing the execution process of smart contracts.

03 Personalized dApps experience

Deep user customization: AI agent analyzes user behavior and Preferences, provide highly personalized services and content recommendations for dApps, and create a unique user experience.

Intelligent chatbots and assistants: Integrate advanced AI chatbots to provide users with real-time and efficient support and interaction, enhancing the usability of the decentralized platform and convenience.

04 Data Privacy and Security Reinforcement

Intelligent anomaly detection: AI agents can monitor areas in real time Blockchain transactions and user activities, intelligently identify and prevent potential security threats and fraud.

Data privacy protection: Through advanced data management technology, AI agents ensure the security and privacy of user data while maintaining the transparency and credibility of the blockchain system .

05 Interoperability and scalability improvement

Cross-chain interaction optimization: AI agent Achieve seamless interoperability between blockchain networks and promote smooth transfer of cross-chain data and assets.

Transaction processing and resource optimization: They significantly improve the scalability and performance of decentralized networks by intelligently optimizing transaction processing processes and resource allocation.

06 Enhance supply chain transparency and traceability

AI agents can deeplyAnalyze and verify data at each stage in the supply chain to achieve full transparency and ensure the authenticity and traceability of commodity sources.

With the help of AI technology, supply chain operations can be optimized and become more efficient in predicting demand, intelligent inventory management, and reducing delays.

07 Intelligent Content Creation and Planning

AI agents can not only help decentralized platforms ( Such as social media dApps) automatically generate and curate content, and also ensure that the content accurately matches user needs and provides a personalized and engaging experience.

In terms of content management, AI agents can perform decentralized content review, effectively identify and filter out inappropriate or harmful content, and ensure the purity of platform content. sex.

08 Medical Health and Autonomous Identity Management

In-depth analysis of health data with the help of AI agents , users can obtain more personalized medical advice and predictive health management solutions.

With the support of blockchain technology, AI agents help users achieve self-sovereign identity management. Users can fully control their personal information and credentials to ensure data security. Security and privacy.

Integrating AI agents with Web3 technology not only optimizes the decision-making process and automates the process, but also brings personalized experience to users while significantly improving Improves security and ensures cross-chain interoperability. This combination fully leverages the advantages of AI and blockchain technology to jointly build a more intelligent, efficient and user-friendly decentralized ecosystem.