#01-What Are AI Agents?
You can think of it as a super-smart robotic assistant (like Iron Man’s Jarvis), equipped with powerful cognitive and learning abilities.This robotic assistant not only understands human language but also continuously enhances its skills in a specific field through learning and data analysis.
Currently, most of the large language models (LLMs) we use operate in a zero-shot prompt mode, which is akin to writing an essay in an exam. After entering prompt information in the dialogue box, the model outputs results based on that prompt information in one go, without any “editing” during the process.
With the introduction of agent workflows, we can require LLMs to perform multiple iterations on the prompt’s objectives, yielding higher quality results, much like how we would revise our writing in private.
#02-Background of AI Agents
The concept of AI Agents originated from developments in the field of artificial intelligence. Initially, AI research focused on enabling machines to perform simple mathematical calculations and logical reasoning. With advancements in computing technology, especially in data processing capabilities and algorithms, modern AI Agents can handle more complex tasks involving language, vision, and even emotional interactions.
#03-Current Research Status of AI Agents
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In the collaborative office sector, the application of AI Agents is particularly prominent. Both domestically and internationally, many companies are actively integrating AI Agents into collaborative office scenarios to enhance work efficiency and reduce labor costs. For instance, some AI Agents can assist in tasks such as document editing, meeting scheduling, and email responses, significantly alleviating employees’ workload. 
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In the entertainment sector, AI Agents also play an important role. For example, some AI chatbots can provide users with personalized entertainment experiences, including chatting, storytelling, and playing music. -
AI Agents can also be used in the online education sector to provide students with intelligent learning assistance and Q&A services. 
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In a paper titled “Generative Agents: Interactive Simulation of Human Behavior” released by a joint team from Stanford and Google, a virtual town was constructed, and its residents were endowed with ChatGPT’s abilities, allowing these residents to have memory, communication, and interaction capabilities to simulate human activities like cooking, washing, and socializing;
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The Google DeepMind team developed a general AI Agent named SIMA, capable of following natural language instructions to perform various tasks in a wide range of 3D virtual environments and video games, such as driving, mining, and shooting; -
A research team from the University of Hong Kong and New York University collaborated on a project named V-IRL, which aims to bridge the perception gap between the digital world and the real world, enabling AI Agents to interact with the real world in a hybrid environment. -
A research team in China developed an AI-based early screening model for pancreatic cancer called PANDA. This model can utilize AI to amplify and identify subtle lesions in plain CT images that are difficult to detect with the naked eye, accurately detecting and diagnosing pancreatic ductal adenocarcinoma and non-pancreatic ductal adenocarcinoma lesions, and can be used for large-scale screening of asymptomatic patient populations. This achievement is expected to improve the early diagnosis rate of pancreatic cancer and provide better treatment outcomes for patients.
However, despite the significant progress made by AI Agents, challenges and risks remain. Among these, data privacy is a crucial issue in AI Agent research. With the widespread application of AI Agents in various fields, how to ensure user privacy and data security, and ensure that AI Agents’ behaviors comply with legal and ethical standards, is an urgent problem that needs to be addressed.
#04-Future Applications of AI Agents
AI Agents can autonomously complete various tasks and exhibit higher levels of personalization across different fields, better meeting the heterogeneous needs of people.
AI Agents can analyze traffic data and real-time road conditions, providing scientific basis for traffic management and planning, improving traffic efficiency, reducing safety hazards, accelerating emergency responses, alleviating parking pressure, and optimizing road resources. Moreover, AI Agents can leverage their powerful computing capabilities to process large amounts of traffic data in real-time, ensuring driving safety and making autonomous driving possible.
AI Agents can autonomously interact and communicate with medical systems and patients, simulating human language and behavior to provide personalized medical services. They can assist doctors in diagnosing diseases, analyzing pathological slices, and formulating treatment plans, thereby improving medical efficiency and quality.
With the development of smart home technology, AI Agents can leverage their powerful learning capabilities to become “smart housekeepers,” helping people manage household devices and improving quality of life.
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Review: Li Guoqing
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