Author: OKC Research Institute
In 1966, MIT computer scientist Joseph Weizenbaum created a program named ELIZA, which could simulate human interaction through a set of rules and language structures. Although ELIZA's functions were very basic and lacked true understanding, it sparked endless imagination about the potential of human-computer interaction, leaving a remarkable mark in the history of natural language processing and becoming one of the starting points for the development of modern artificial intelligence.
Fast forward to 2024, the name 'Eliza' reappears in heated discussions in the context of Web3. This time, it is no longer a simple tool for simulating dialogue but a foundational framework supporting the construction and operation of agents in the Web3 world.
It allows developers to quickly create multifunctional AI agents that can automatically complete transactions, execute governance tasks, and even analyze on-chain data in real time, potentially transforming the way people interact with blockchain.
Pic Source: https://elizaos.ai
Why has Eliza suddenly become popular?
Technology is an old trope, but trends tell a new story
Behind the rise of AI agents is the 'century marriage' of AI and blockchain. Moving from technical concepts to practical applications, this has become a major hotspot in the crypto field. These agents are not just tools but also 'independent economies.' By autonomously executing tasks, they are redefining 'participation' and 'value' in Web3. Just as ELIZA opened the door to human-computer interaction, today's Eliza framework is reshaping the relationship between people and on-chain networks.
A new type of decentralized participant
Another attractive point of AI agents is their seamless integration with the decentralized economy. Relying on the Eliza framework, developers can build powerful agents, such as ai16z—a virtual venture capital fund capable of real-time analysis and summarization of information and documents exchanged by users in specific social channels, making investment decisions based on different message weights and completing on-chain interactions.
This model showcases a new possibility: humans are not the only economic participants; agents can also become key nodes in the value chain.
Pic Source: https://elizaos.ai
From framework to functionality: the engine behind AI agents
The AI Agent framework is the core tool for building and running AI agents, enabling developers to quickly deploy agents, while users can access unprecedented services and value through these agents. From investment assistance to content generation, the functionalities of agents are rapidly expanding, and the underlying framework has become a key driving force for innovation in the crypto industry. Compared to NFTs or memes, agents may exhibit stronger long-term value potential due to their functionality and sustainable business models.
An interesting example is how the Eliza framework enables ai16z to achieve automated investment. Based on the Eliza framework, ai16z created a virtual venture capital fund that utilizes agent-driven investment decisions. It is not just simple buy and sell operations, but instead analyzes on-chain data through machine learning models to provide real-time insights for the community. Eliza, with its modular design and open-source ecosystem, covers application areas including social integration, asset issuance, and analytical insights, demonstrating the diverse potential of the AI Agent framework. This not only improves the efficiency of on-chain governance but also has the potential to elevate the concept of decentralized autonomy to new heights.
The 'Elizas' in Web3: what trends might they ignite?
Although the agent market is still in its early stages, the potential is undeniable as AI frameworks like Eliza become more widespread. With the continuous evolution of the AI Agent framework, we can anticipate the following trends:
The new economic form of agents
These AI agents can not only perform tasks but also dynamically adjust operations through real-time data, such as optimizing network resource allocation, achieving both cost-saving and profit-making.
Strengthening on-chain communities
Agents can provide on-chain communities with real-time information integration and analytical support, helping users participate in on-chain governance and economic activities more quickly and accurately.
Cross-border integration of technology
As the AI Agent framework integrates with decentralized storage and computing platforms, the functionalities of these agents will become even more diverse. From financial services to on-chain gaming, agents may be ubiquitous.
The rise of agents not only changes the way users interact with technology but also introduces new asset classes. These digital entities are gradually forming a market that is tradable and investable. Similar to NFTs, agents provide users with direct economic benefits through tokenization, while attracting more long-term investors with innovative functional services.
Just as every wave of technological revolution in history has shown, the AI Agent framework is transforming complex technology into simple and user-friendly tools, opening new frontiers for Web3.
But even with a focused and clear direction, the challenges faced by AI agents are not small:
Security issues: How to prevent agents from being exploited by hackers and avoid asset losses?
Centralization risks: Although agents are decentralized, the development and control of the framework are still in the hands of a few teams.
Ethical controversies: When agents make independent decisions, who is responsible when something goes wrong?
From observers to participants, why AI agents deserve your attention
AI agents are driving Web3 into a new stage, enhancing efficiency while redefining the concept of 'participation.' If DeFi was the protagonist of the last wave, AI agents may become the core driving force for the next decade.
As AI expert Andrew Ng said, the value of AI lies in its 'task orientation'—focusing on completing high-value tasks, improving efficiency, and benefiting users. AI agents are an extension of this concept: they simplify on-chain operations, allowing ordinary users to participate efficiently.
Instead of merely being an observer, consider: how will you coexist with agents when humans and agents coexist on-chain?
