LLM Powered Autonomous Agents
Researchers are exploring the use of large language models (LLMs) as the core controller for autonomous agents. These agents can break down complex tasks into smaller subgoals, reflect on past actions, and learn from mistakes to improve performance. They also have short-term memory for in-context learning and long-term memory for retaining information over extended periods. Additionally, they can use external tools and APIs to access extra information.
Researchers are exploring the use of large language models (LLMs) as the core controller for autonomous agents. These agents can break down complex tasks into smaller subgoals, reflect on past actions, and learn from mistakes to improve performance. They also have short-term memory for in-context learning and long-term memory for retaining information over extended periods. Additionally, they can use external tools and APIs to access extra information.
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Why it matters: This matters because LLM-powered autonomous agents could potentially solve complex problems more efficiently than current AI systems, making them a significant area of research for engineers and researchers working on AI.
Source: https://lilianweng.github.io/posts/2023-06-23-agent/
This article was originally published at: https://lilianweng.github.io/posts/2023-06-23-agent/