In 1966, Joseph Weizenbaum, a computer scientist at MIT, created a program called ELIZA, which can imitate user input text through some rules and language structures to achieve simple human-computer interaction. Although ELIZA's functions are very basic and do not have real understanding ability, it has inspired people's unlimited imagination of the potential of human-computer interaction. However, this groundbreaking experiment left a glimpse in the chapter of natural language processing and became one of the starting points of the development of modern artificial intelligence.
Fast forward to 2024, the name "Eliza" has once again appeared in the context of Web3. This time, it is no longer a gadget to simulate conversations, but an underlying framework that supports the construction and operation of intelligent agents in the Web3 world.
It allows developers to quickly create versatile AI agents that can automatically complete transactions, perform governance tasks, and even analyze on-chain data in real time, and is expected to completely change the way people interact with blockchain.
Pic Source：https://elizaos.ai
Why is Eliza suddenly popular?
Technology is an old story, but the trend is the new story
Behind the rise of AI agents is the "marriage of the century" between AI and blockchain. From technical concepts to practical applications, it has become a hot spot in the encryption field. These agents are not only tools, but also "independent economies". By performing tasks autonomously, they are redefining "participation" and "value" in Web3. Just as ELIZA opened the door to human-computer interaction, today's Eliza framework is also reshaping the relationship between people and on-chain networks.
New decentralized participants
Another attraction of AI agents is that they can be seamlessly integrated into the decentralized economy. Relying on the Eliza framework, developers can build powerful agents, such as ai16z, a virtual venture capital fund that can analyze and summarize the information and files exchanged by users in special social channels in real time, make investment decisions based on different message weights, and complete on-chain interactions.
This model shows a new possibility: humans are not the only economic participants, and 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, allowing developers to quickly deploy agents, and users can obtain unprecedented services and value through these agents. From investment assistance to content generation, the functions of agents are rapidly expanding, and the framework behind them has become a key driver of innovation in the crypto industry. Compared with NFTs or memes, agents may show stronger long-term value potential in the future due to their functionality and sustainable business model.
An interesting example is how the Eliza framework enables ai16z to automate investment. Based on the Eliza framework, ai16z created a virtual venture capital fund that uses agents to drive investment decisions. It is not a simple buy and sell operation, but analyzes on-chain data through machine learning models to provide real-time insights to the community. With its modular design and open source ecology, Eliza's application areas cover 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 push the concept of decentralized autonomy to a new level.
"Eliza" in Web3: What trends may have been set off?
Although the agent market is still in its early stages, with the popularization of AI frameworks like Eliza, its potential cannot be ignored. As the AI Agent framework continues to evolve, we can foresee the following trends:
A new economic form of intelligent agents
These AI Agents can not only perform tasks, but also dynamically adjust operations through real-time data, such as optimizing network resource allocation, saving money and making money at the same time. .
Strengthening of on-chain communities
Intelligent agents can provide real-time information integration and analysis support for on-chain communities, helping users participate in on-chain governance and economic activities more quickly and accurately.
Cross-border integration of technology
With the integration of AI Agent frameworks with decentralized storage and computing platforms, the functions of these agents will become more diversified. From financial services to on-chain games, agents may be everywhere.
The rise of agents has not only changed the way users interact with technology, but also brought new asset classes. These digital entities have gradually formed a tradable and investable market form. Similar to NFTs, agents provide users with direct economic benefits through tokenization, while attracting more long-term investors through innovative functional services.
Like every wave of technology in history, the AI Agent framework is transforming complex technologies into simple and easy-to-use tools, opening up new boundaries for Web3.
But even with a clear direction to focus on, AI agents still face considerable challenges:
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 disputes: When agents make independent decisions, who is responsible if something goes wrong?
From observers to participants, why AI agents deserve your attention
AI agents are pushing Web3 into a new stage, not only improving efficiency but also redefining the concept of "participation". If DeFi was the protagonist of the last wave, then 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 so that ordinary users can participate efficiently.
Instead of just being a bystander, it is better to think: When humans and agents coexist on the chain, how will you coexist with them?
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