AI Agent Track: The Evolution from Virtual Assistants to Digital Beings

As time progresses to 2025, AI technology has become deeply ingrained in people's minds, but many still have misunderstandings about the concept of Agent( agent). A true "AI Agent" project needs to follow the following workflow: perception, thinking, action.

Taking automated cryptocurrency investment as an example, its operation is as follows:

1. Perception: Collect the latest cryptocurrency news.
2. Reflection: Analyze the impact of news on specific cryptocurrencies
3. Action: Execute buy or sell operations based on the analysis results.

So, is the widely known ChatGPT considered an AI Agent? Although ChatGPT considers itself an AI Agent, it is more like an intelligent dialogue component, lacking complete multimodal perception and the ability to operate in a physical environment.

In contrast, AI Agents typically have the following characteristics:

• Focus on solving problems in specific areas
• Able to obtain more data from the real world

Therefore, the complete definition of AI Agent should include:

1. Adopt the "Perceive-Analyze-Act" processing flow
2. Targeted solutions for a specific vertical issue
3. Use more data from the real physical world

Currently, AI Agents are mainly applied in the following fields:

1. AI Investment: Cryptocurrency trading based on real-time news analysis
2. AI Virtual Companion: A conversational system with specific personality settings
3. Opinion Output: Provide analysis and commentary on specific topics
4. Virtual Idol: AI-based Digital Artist
5. Prediction Market: Probability forecasting for specific events
6. AI Resource Sharing: Integrating various AI services for convenient access
7. Other vertical applications: such as AI painting, music creation, etc.

At the same time, multiple AI Agent development frameworks such as AI16Z, Virtual, AVA, etc. have emerged, providing developers with tools for rapid deployment of AI Agents. These frameworks not only offer technical support but also integrate token issuance functionalities, allowing AI Agent projects to more easily enter the cryptocurrency market.

However, this integration has also brought about some controversies. Some traditional AI developers believe that certain AI Agent projects focus too much on token issuance while neglecting technological innovation. However, supporters argue that the cryptocurrency ecosystem provides a rapid market validation opportunity for AI innovation, which helps promote industry development.

The rapid development of the AI Agent field has sparked people's thoughts about the future: as AI technology continues to advance, how will we define the relationship between artificial intelligence and humans? This question may find an answer in the coming decades.