Professional Agents -- Evolving Large Language Models into Autonomous Experts with Human-Level Competencies
It proposes a conceptual framework for applying LLMs to professional domains, but it is incremental as it builds on existing LLM capabilities without presenting new empirical results.
This position paper introduces Professional Agents (PAgents), a framework using large language models to create autonomous agents with professional-level competencies, aiming to reshape professional services and potentially achieve artificial general intelligence.
The advent of large language models (LLMs) such as ChatGPT, PaLM, and GPT-4 has catalyzed remarkable advances in natural language processing, demonstrating human-like language fluency and reasoning capacities. This position paper introduces the concept of Professional Agents (PAgents), an application framework harnessing LLM capabilities to create autonomous agents with controllable, specialized, interactive, and professional-level competencies. We posit that PAgents can reshape professional services through continuously developed expertise. Our proposed PAgents framework entails a tri-layered architecture for genesis, evolution, and synergy: a base tool layer, a middle agent layer, and a top synergy layer. This paper aims to spur discourse on promising real-world applications of LLMs. We argue the increasing sophistication and integration of PAgents could lead to AI systems exhibiting professional mastery over complex domains, serving critical needs, and potentially achieving artificial general intelligence.