AI Agents

【New Intelligence Introduction】 AI Agents are a hot topic in the field of large models. Users can introduce multiple LLM Agents with different roles to participate in actual tasks. Agents will engage in various forms of dynamic interactions such as competition and collaboration, thereby producing amazing group intelligence effects. This article introduces the large model mind interaction CAMEL framework (Camel) from the KAUST research team. The CAMEL framework is the earliest well-known project of autonomous agents based on ChatGPT, and has been accepted by the top artificial intelligence conference NeurIPS 2023.

Abstract: The multi-AI agent model is a powerful artificial intelligence architecture that uses the collaboration and interaction between multiple agents to solve complex problems, perform diverse tasks, and simulate complex system behaviors. In this model, each agent has independent perception, decision-making, and action capabilities, and optimizes the overall system goals through mutual collaboration and information sharing.

At present, the industry generally believes that applications based on large models are concentrated in two directions: RAG and Agent. Regardless of which application, designing, implementing, and optimizing applications that can fully utilize the potential of large models ( LLM ) requires a lot of effort and expertise. As developers begin to create increasingly complex LLM applications, the development process inevitably becomes more complicated. The potential design space of such a process can be huge and complex. The article " How to Build Apps Based on Large Models " provides an exploratory basic framework for large model application development, which can basically be applied to RAG and Agent. However, is there anything unique about agent-oriented large model application development? Is there a large model application development framework focused on Agent?

Many people may wonder, Agent seems to be not that far from LLM, so why is Agent so popular recently, and why is it not called LLM-Application or other words? This has to start with the origin of Agent, because Agent is a very old term, and can even be traced back to the remarks of Aristotle and Hume. In a philosophical sense, agent refers to an entity with the ability to act, and the word agent refers to the exercise or manifestation of this ability. In a narrow sense, agent usually refers to the manifestation of intentional action; accordingly, the word agent refers to an entity with desires, beliefs, intentions and the ability to act. It should be noted that agents include not only human individuals, but also other entities in the physical and virtual worlds. Importantly, the concept of agent involves the autonomy of individuals, giving them the ability to exercise their will, make choices and take actions, rather than passively responding to external stimuli.

Generative AI is entering the agent era, with “agentic AI” or “AI agent ” being the buzzwords right now . The agent architectures and early use cases we see today represent only the beginning of a broader transformation that promises to redefine the human-machine dynamic, with profound implications for enterprise applications and infrastructure .

Imagine that every decision in an enterprise can be based on in-depth data analysis, customer service can be personalized to each users needs, and internal processes are automated to the point where human supervision is almost unnecessary. This is not a futuristic fantasy, but an enterprise revolution led by AI Agents , which is rapidly changing our business world.

AI Agent is a virtual assistant powered by artificial intelligence that can help automate processes, generate insights, and improve efficiency. This article mainly introduces 6 different AI Agents.

AI agents are a key technological advancement that is reshaping business dynamics. Learn how these agents operate and discover their key benefits including efficiency, scalability, and cost-effectiveness. We will explore real-world examples of agents and their applications in various fields, paving the way for future AI trends and their impact on customer experience.

So, what exactly is an AI agent? Tech giants and startups are exploring the potential of AI agents. However, some companies confuse AI assistants and AI chatbots with fully developed autonomous AI agents. AI Agents consist of a set of instructions and AI models, as well as tools that can be used. Through these instructions, tools, and AI models, AI Agents can focus the power of AI models on specific tasks and provide the right information needed to achieve better results.

In 2024, the concept of AI Agents has emerged as a pivotal advancement in the application of large language models (LLMs), akin to harnessing fire and flint to propel human civilization into a new era. While the prominence of big models has plateaued, resulting in a winner-takes-all landscape, AI Agents represent the most effective utilization of these models, addressing the inherent limitations of LLMs in targeted applications. By leveraging the strengths of AI Agents, organizations can navigate complexity and drive innovation, marking a significant milestone in the evolution of artificial intelligence.