“As foundational models become increasingly powerful, developing applications is becoming simpler, with intelligent agents being the simplest. Creating a good intelligent agent typically does not require coding; as long as the workflow is clear and paired with a proprietary knowledge base, it becomes a highly valuable intelligent agent, easier than creating a webpage in the internet era.”
At the recently held 2024 World Artificial Intelligence Conference and the High-Level Conference on Global Governance of Artificial Intelligence, Baidu’s founder, chairman, and CEO Li Yanhong stated that intelligent agents are the development direction of artificial intelligence applications that Baidu is most optimistic about.
Intelligent agents are systems capable of autonomously perceiving their environment, making decisions, and executing actions, typically relying on large language models as their core decision-making and processing units, possessing basic characteristics such as autonomy, reactivity, adaptability, and interactivity.
In fact, these intelligent agents based on large models can be divided into two key types based on their primary functions: conversational agents and task-oriented agents.
A significant advantage of conversational agents is their ability to exhibit human-like capabilities in discussions. By considering multiple factors such as tone, speaking style, domain knowledge, viewpoints, and personality traits, conversational agents can achieve nuanced and contextual interactions. In applications such as customer service chatbots, conversational agents can utilize role prompts to shape natural and empathetic responses, and their outstanding language understanding and generation capabilities make conversations smooth and adaptive. Furthermore, conversational agents open new avenues for interactively collecting information reflecting human discussions, serving as informed advisors or experts in fields like healthcare or law, providing valuable advice and information.
Unlike conversational agents, task-oriented agents focus on achieving set goals and completing workflows. These goal-driven systems excel at breaking down high-level tasks into more manageable sub-tasks, leveraging their powerful language modeling capabilities to analyze prompts, extract key parameters, formulate plans, call APIs, perform operations through integrated tools, and report results, enabling them to automatically handle multifaceted objectives.
In recent years, the continuous maturation of artificial intelligence technology has brought tremendous changes to people’s work and lives, especially the rapid development of generative AI technology represented by large models, which has led a new technological revolution. In this revolution, intelligent agents, as pioneers, have transitioned from theory to practice.
First, virtual assistants. Examples include Siri, Google Assistant, and Alexa, which can assist users in setting reminders, answering questions, controlling smart home devices, greatly enhancing convenience in life.
Second, the software industry. In software development and application fields, intelligent agents simplify processes through more efficient task handling capabilities, saving valuable time and resources, thus promoting rapid development in the software industry.
Third, autonomous driving. Autonomous vehicles and drones can use intelligent agents to perceive their surroundings, make driving decisions, and achieve safe navigation, indicating that this technology will bring disruptive changes to the transportation field.
Fourth, healthcare. Intelligent agents in the medical field can assist professionals in diagnosing diseases, analyzing medical images, and managing patient records, improving the efficiency and accuracy of medical services, providing better treatment experiences for patients.
Fifth, cybersecurity. Intelligent agents can effectively protect systems from cyber attacks by analyzing network traffic patterns and identifying abnormal behaviors, playing a key role in security threat detection and response, thus providing robust support for cybersecurity.
Sixth, education. Intelligent agents in education can provide customized learning experiences, adjusting teaching content and pace according to student needs, and offering instant feedback and assessments, optimizing the educational process and enhancing teaching quality.
In summary, these examples fully demonstrate the wide application and profound impact of intelligent agents across multiple fields. However, it is worth noting that despite the enormous potential shown by intelligent agents in many areas, they also face some challenges and limitations, which we will examine specifically:
First, intelligent agents typically lack the common sense or deep understanding of the world that humans possess. This means they may encounter difficulties in executing tasks that require background knowledge or situational judgment. For example, when faced with novel or unforeseen situations, intelligent agents might fail to accurately identify the essence of the problem, leading to incorrect decisions.
Second, intelligent agents may encounter ethical dilemmas during decision-making. Since their decisions are based on data analysis and machine learning algorithms, this may lead them to replicate or even amplify biases and inequalities present in the training data.
Third, the learning and decision-making capabilities of intelligent agents depend on data. When encountering new types of data or insufficient data volumes, the performance of intelligent agents may be affected. This is because most machine learning models require large volumes of high-quality data to optimize their predictive and decision-making capabilities. In situations of data scarcity or poor quality, the outputs of intelligent agents may become unreliable, thus reducing their accuracy in real-world environments.
Therefore, to address these issues, continuous optimization and improvement of the design and application methods of intelligent agents are required to overcome these limitations and unleash their maximum potential.
With the continuous advancement of technology, we have reason to believe that future intelligent agents will become smarter and more human-like, becoming an indispensable part of human society. As for the future, how intelligent agents will reshape our world, let’s wait and see.
Disclaimer:
This article is an observational or commentary piece published by a third-party self-media author. All text and image copyrights belong to the author, and only represent the author’s personal views, unrelated to Beijing Internet of Things Intelligent Technology Application Association. The article is for reference only, and readers are advised to verify the relevant content themselves.
