An Agent can be understood as an intelligent entity.
As early as the 1950s, Alan Turing expanded the concept of “intelligence” to artificial entities and proposed the famous Turing Test.These artificial intelligence entities are commonly referred to as agents.
The concept of “agent” originates from philosophy, describing an entity that possesses desires, beliefs, intentions, and the ability to take action.
A paper from Stanford University titled “Generative Agents: Interactive Simulacra of Human Behavior” delves into the memory, response, and planning of AI agents.
So, what is an AI agent?
In simple terms, it is an agent empowered by AI technology that becomes smarter, can perceive its surroundings, and is capable of independent thought and action.
Have you ever used a conversational large model (LLM), such as Wenxin Yiyan, Kimi Chat, or Zhizhu AI? The difference between an AI agent and a conversational model is that you don’t have to keep telling it what to do; just give it a goal, and it will find a way to help you accomplish it automatically.
Therefore, large models (LLMs) require a lot of diverse data, which helps them learn to communicate, learn, think, and reason like humans.
However, it is not perfect and often has strange ideas or is influenced by the environment; at this point, an AI agent developed based on a large model can further refine the problem.
For example, have you used Xiao Ai Tong Xue? If you feel unwell, in the past, you would tell it, “I don’t feel well,” and it would only tell you to go to the hospital and pay attention to protection. A smarter AI agent would act differently.
It can check your temperature and other health indicators, combine information from the internet, analyze it, and tell you: You might have a fever.” Next, it can even help you automatically write a leave request.
AI Agents are considered the next direction for OpenAI’s efforts.
Andrej Karpathy, co-founder of OpenAI, said at a recent public event, “Compared to model training methods, OpenAI is currently more focused on changes in the agent field. Whenever a new AI agents paper comes out, the team gets excited and discusses it seriously.”
In the field of artificial intelligence, this term has been given a new meaning: intelligent entities characterized by autonomy, reactivity, proactivity, and social capabilities.
An AI Agent is designed to have the ability to think and act independently.
You only need to provide a goal, such as writing a game or developing a webpage, and it will generate a task sequence based on the environment’s reactions and its own introspection to start working.
It’s as if artificial intelligence can self-prompt and feedback, continuously developing and adapting to achieve the goals you set in the best possible way.
A complete agent is like the process of humans interacting with their surroundings; it consists of two parts: one part is the agent itself, and the other part is its environment.
The agent is like a human living in the physical world, while the physical world is its external environment. Humans perceive the surrounding world, understand the hidden information in the environment, and combine their memory and understanding of the world to plan, make decisions, and take action; actions will also affect the environment, generating new feedback.
Humans make decisions again based on feedback, forming a continuous loop.
This is the magic of AI agents.
So, why is it important?
Firstly, AI agents will lead the software industry into a new era.
In the past, programming required writing a large number of temporary files, testing plans, and keeping them for future use; now programming can be fully automated, with costs almost zero.
This means that software tasks that used to require millions of people can now be completed by a small number of individuals.
However, its practical application still requires further training to become smarter.
For instance, a clothing design company faces a major challenge: when mass-producing clothing, it needs to design and create multiple samples, a process that traditionally relies entirely on manual labor.
Now, AI agents can intervene in this process, but to what extent can they handle it? Is the accuracy high enough? These all require further exploration and testing.
Thus, the development of agents in the country has not yet reached its true potential, with most being simple chatbots.
They lack reflection, planning, and environmental perception abilities, which are precisely the core elements of advanced AI agents.
If you want to create your own innovative work with AI agents, feel free to contact Teacher Entropy!
– Long press the QR code to add the teacher on WeChat –
Event Consultation | Innovation Consultation | Cooperation Contact
Click the link below to follow Entropy Future and learn more about public welfare activities, background enhancement, international competitions, and educational knowledge!
Recommended readings:
Summary of 2025 International Competitions and Dates
Analysis of Popular STEM Majors and Employment Directions in the U.S.!
What is Software Copyright? What Benefits Can It Bring to Students?