Artificial intelligence (AI) large language models (LLM) like OpenAI’s hit GPT-3, 3.5, and 4, encode a wealth of information about how we live, communicate, and behave, and researchers are constantly finding new ways to put this knowledge to use.
A recent study conducted by Stanford University researchers has demonstrated that, with the right design, LLMs can be harnessed to simulate human behavior in a dynamic and convincingly realistic manner.
The study, titled “Generative Agents: Interactive Simulacra of Human Behavior,” explores the potential of generative models in creating an AI agent architecture that remembers its interactions, reflects on the information it receives, and plans long-and short-term goals based on an ever-expanding memory stream. These AI agents are capable of simulating the behavior of a human in their daily lives, from mundane tasks to complex decision-making processes.
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