Despite significant advancements in software over the past few decades, it still remains somewhat “clumsy” in many respects. When completing tasks on a computer, you need to tell the device which application to use. For example, you can write a business proposal using Microsoft Word and Google Docs, but they cannot help you send emails, share selfies, analyze data, plan parties, or buy movie tickets. Even the best websites can only partially understand your work, personal life, interests, and relationships, and their ability to utilize this information to serve you is limited. However, all of this will change dramatically in the next five years. You will no longer need to use different applications for different tasks. You will simply tell your device what you want to do in everyday language, and the software will be able to respond in a personalized manner based on the amount of information you are willing to share, as it will deeply understand your life. In the near future, anyone connected to the internet will be able to have a personal assistant powered by AI, whose capabilities will far exceed current technology levels. This software, which can understand natural language and complete various tasks based on its understanding of the user, is called an “Agent.”

In the fields of computer science and artificial intelligence, an Agent is typically defined as an autonomous computing entity that can perceive its environment, make decisions, and take actions to achieve its goals. Agents can be physical entities, such as robots, or virtual entities, such as software programs. Their main characteristics include autonomy, social ability, reactivity, and proactivity. These characteristics enable Agents to operate autonomously in complex environments, interact with users or other Agents, and respond promptly to changes in the environment.

The following is a basic process for building Agent applications based on a platform:

1. Platform Selection and Registration: First, register an account and log in to the Qianfan large model development and service platform. This platform provides a rich library of models and tools, supporting developers in model training, inference, and application development.

2. Model Selection and Training: Based on application requirements, select an appropriate base model for training on the platform. Adjust model parameters and optimize training strategies to improve the model’s accuracy and stability.

3. Agent Design and Development: In the development environment provided by the platform, design the architecture and processes of the Agent. Utilize the APIs and toolsets provided by the platform to implement the Agent’s perception, reasoning, and execution functions. Additionally, design the interface and interaction based on application requirements.

4. Integration and Testing: Integrate the designed Agent into the application and conduct functional, performance, and user experience testing. Ensure that the Agent can operate stably in practical applications and meet user needs.

5. Deployment and Release: Deploy the tested Agent application to the production environment and promote and market it on application stores or online platforms. Meanwhile, continuously collect user feedback and iterate for optimization.

In the development of large model applications, the Agent technology framework is the core that supports the entire development process. A complete Agent technology framework usually includes four main elements: perception, decision-making, action, and learning. The perception element is responsible for collecting environmental information; the decision-making element makes decisions based on the perceived information; the action element is responsible for executing decisions; and the learning element enables the Agent to continuously learn from experience, optimizing its behavior and decision rules. Additionally, the Agent technology framework also includes various memory mechanisms, core skills for invoking tools, and reasoning engines as key components. These components work together to enable the Agent to achieve efficient and autonomous operation in complex environments.

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