Building agents with LLM (large language model) as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs; it can be framed as a powerful general problem solver.
Agent System Overview In a LLM-powered autonomous agent system, LLM functions as the agent’s brain, complemented by several key components:

Lilian Weng is a machine learning researcher and writer who shares insights, research findings, and tutorials on machine learning, artificial intelligence, and data science. Through articles, blog posts, and research summaries, Lilian Weng explores topics such as deep learning, natural language processing, and reinforcement learning. Readers can learn about state-of-the-art algorithms, practical applications of machine learning, and trends shaping the field of AI.

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LLM Powered Autonomous Agents with LLM as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs.