This article is translated from Sonny Young's in-depth industry analysis article "Why AI Agents Will Become the Next Hot Narrative of Web3?" published on Medium, with some minor deletions that do not affect the author's intention. The article starts from the function of AI agents, analyzes the advantages and development direction of AI agents, and introduces its wide range of applications in Web3.0. Come and take a look with Xiao Wan!
What is an AI agent?
Imagine that you have created a game similar to "Mario Kart". Mario, as an AI agent in the game, has a significant impact on the outcome of the game. He needs to make decisions throughout the game, such as when to accelerate, turn, and jump, in order to cleverly avoid obstacles, overtake other racers, and ultimately win the game. In this example, the entire game environment and the behavior of other racers constitute the environment of the AI agent. The AI agent will make the best decision based on this information. For example, if the road ahead turns left, the intelligent agent will turn left.
The essence of an AI agent is a system that can perceive its environment, make decisions based on a given goal, and take actions. 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 an AI agent is its adaptability. It is able to "learn", which means that it can continuously improve its decision-making process through interaction with the environment. For example, after many games, it may learn how to better avoid obstacles or find the best racing line, demonstrating its ability to evolve and adapt.
In summary, an AI agent is an AI system that can perceive and understand its environment, make decisions, take actions, and continue to learn and evolve.
AI Agents - The Next Hot Topic
In the development of large language models, the next evolution will proceed in two directions. On the one hand, it is "downward" to focus on updating and improving the underlying system. On the other hand, it is "upward" expansion, enhancing productivity from a higher dimension by increasing complexity, intelligence and automation - this is essentially the development of agent models. A typical agent module unit integrates multiple components such as memory, planning, execution and reflection, making it more intelligent than the traditional large language model interaction mode.
Not only that, in order to meet various needs, people continue to add exciting new features to these systems, thus constantly broadening the boundaries of imagination. Some outstanding innovative ideas, such as integrated search engines and compiler functions, have been gradually realized in research in recent months.
Although a single agent is powerful and easy to use, OpenAI GPTs represents the future of the AI business model based on independent agents. 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 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 imagination should be extended accordingly. The potential for AI evolution is huge, and this infinite 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. Here, "users" refers to the vast 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 early stages 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, 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 not only democratize the technology, but also strengthen the sovereign status 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, and provides users with a new choice with transparency, security, and empowerment at its core.
Second, the introduction of Web2 users is crucial to promoting the widespread application and mainstream acceptance of Web3. Web3 is not limited to the financial sector. It has the potential to revolutionize many fields such as healthcare, supply chain management, voting systems, content creation, etc. With the onboarding of Web2 users, we will further expand the user base and ecosystem of decentralized applications, and this network effect will accelerate the development and maturity of the decentralized network. This widespread adoption not only validates the utility and vitality of Web3, but will also inspire more investment, research, and innovation in decentralized technologies to build a more robust, inclusive, and vibrant digital future.
Massive Adoption and Market Transformation
In today's market landscape, many teams are quietly investing in the development of AI agent projects in the Web3 space. As competition in this space intensifies, a forward-looking strategic vision becomes essential to navigate this turbulent market. Obviously, in this environment, the core of efficiency lies in precise market transformation, focusing on cultivating a unique and outstanding AI agent project, rather than dispersing 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 energy on developing an outstanding AI agent project, companies can take the lead in this evolving Web3 transformation. Furthermore, this strategy goes beyond just meeting the needs of the Web3 community, and has a broader 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 facilitate seamless integration and adoption of decentralized technologies by a global audience. This will position companies as industry leaders in the transformative digital space, ensuring their continued prosperity in this market full of opportunities and challenges.
Endless Possibilities
Combining AI agents with Web3 technologies not only creates powerful synergies, but also greatly enhances the functionality of decentralized applications (dApps), improves user experience, and drives innovation. Here are the specific ways AI agents integrate with Web3 technologies and the benefits they bring:
01 Decentralized Self-Organizations (DAOs)
Intelligent decision support: AI agents provide DAOs with key insights through in-depth data analysis, helping them make more informed and efficient decisions.
Automated governance processes: AI agents automate governance processes including voting and proposal evaluation, enabling DAOs to respond to various situations more quickly and effectively.
02 Smart Contracts
Advanced automation capabilities: AI agents can trigger and manage smart contracts based on complex conditions and data inputs, enabling more complex and sophisticated process automation.
Predictive analysis and optimization: Using advanced machine learning models, AI agents can predict the results of contract execution, thereby optimizing the execution process of smart contracts.
03 Personalized dApps experience
Deep user customization: AI agents provide highly personalized services and content recommendations for dApps by analyzing user behavior and preferences, creating a unique user experience.
Smart chatbots and assistants: Integrate advanced AI chatbots to provide users with real-time, efficient support and interaction, enhancing the ease of use and convenience of decentralized platforms.
04 Data Privacy and Security Reinforcement
Intelligent Anomaly Detection: AI agents can monitor blockchain transactions and user activities in real time, 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 agents achieve seamless interoperability between blockchain networks and promote the 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 and resource allocation.
06 Enhance supply chain transparency and traceability
AI agents can deeply analyze and verify data at each stage of the supply chain to achieve full transparency and ensure the authenticity and traceability of the source of goods.
With the help of AI technology, supply chain operations can be optimized, and demand forecasting, intelligent inventory management, and delay reduction become more efficient.
07 Intelligent content creation and planning
AI agents can not only automatically generate and curate content for decentralized platforms (such as social media dApps), but also ensure that these contents accurately match user needs and provide personalized and engaging experiences.
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.
08 Healthcare and autonomous identity management
With the help of AI agents' in-depth analysis of health data, 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, allowing users to fully control their personal information and credentials, ensuring data security and privacy.
The integration of AI agents with Web3 technology not only optimizes the decision-making process and automates the process, but also brings a personalized experience to users, while significantly improving security and ensuring cross-chain interoperability. This combination gives full play to the advantages of AI and blockchain technology, and jointly builds a more intelligent, efficient and user-friendly decentralized ecosystem.
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