Who is Eliza?

In 1966, MIT computer scientist Joseph Weizenbaum created a program called ELIZA, a program that can mimic 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 capabilities, it stimulates people’s infinite imagination of the potential of human-computer interactions. However, this pioneering experiment left a glimpse in the chapter of natural language processing and became modern artificial.One of the starting points of intelligent development.

Fast forward to 2024, and the name “Eliza” once again appears in the hot topic in the context of Web3.This time, it is no longer a gadget that simulates dialogue, but is the underlying framework in the Web3 world that supports the construction and operation of agents.

It allows developers to quickly create multi-functional 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 did Eliza suddenly become popular?

Technology is an old joke, but trends are 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 topic in the field of encryption.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.

A brand new participant in decentralization

Another attraction for AI agents is that they can seamlessly integrate with the decentralized economy.Relying on the Eliza framework, developers can build powerful agents, such asai16z——A virtual venture capital fund can analyze and summarize the information and documents exchanged by users in a special social channel in real time, make investment decisions based on different message weights, and complete on-chain interactions.

This model demonstrates a new possibility: humans are not the only economic players, and agents can also become key nodes in the value chain.

Pic Source: https://elizaos.ai

From framework to functionality: the behind-the-scenes engine of AI agents

The AI ​​Agent framework is the core tool for building and running AI agents, allowing developers to quickly deploy agents, while users can obtain unprecedented services and value through these agents.From investment assistance to content generation, the functions of the agent are rapidly expanding, and the framework behind it has also become a key driving force for innovation in the crypto industry.Compared with NFT or meme, agents may show stronger long-term value potential in the future due to their functional and sustainable business model.

An interesting example is how the Eliza framework enables ai16z to achieve automated investment.Based on the Eliza framework, ai16z has created a virtual venture capital fund that uses agents to drive investment decisions.It is not a simple buying and selling operation, but analyzing on-chain data through machine learning models to provide real-time insights to the community.With its modular design and open source ecosystem, Eliza demonstrates the diversification potential of the AI ​​Agent framework, including social integration, asset issuance and analytical insights.This not only improves the efficiency of on-chain governance, but also hopes to push the concept of decentralized autonomy to a new level.

“Elizas” in Web3: What trends may have triggered?

Although the agent market is still in its early stages, its potential cannot be ignored as Eliza-like AI frameworks become popular.As the AI ​​Agent framework continues to evolve, we can foresee the following trends:

• The new economic form of the agent

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..

• Strengthening of the on-chain community

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 the AI ​​Agent framework with decentralized storage and computing platforms, the functions of these agents will be more diversified.From financial services to on-chain games, agents may be everywhere.

The rise of agents not only changes the way users interact with technology, but also brings new asset classes.These digital entities have gradually formed a market form that is tradable and investable.Similar to NFT, agents provide users with direct economic benefits through tokenization, while attracting more long-term investors through innovative functional services.

Just 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 that can be focused, AI intelligence faces a lot of tests:

• Security Question:How to prevent the agent from being exploited by hackers and avoid asset losses?

• Centralized risk: Although agents are decentralized, the development and control of the framework are still in the hands of a few teams.

• Ethical Controversy: When an agent makes independent decisions, who will bear the responsibility for the problem?

Why AI agents deserve your attention from observers to participants

AI agents are pushing Web3 into a new stage, not only improving efficiency, but also redefining the concept of “participation”.If DeFi is the protagonist of the previous wave, then AI agents may become the core driving force for the next decade.

As AI expert Andy Ng said, the value of AI lies in “task orientation” – focusing on completing high-value tasks, improving efficiency and benefiting users in an all-round way.AI agents are an extension of this concept:They simplify on-chain operations and allow ordinary users to participate efficiently.

Rather than being just a bystander, think about: How will you coexist with humans and agents when they coexist on the chain?