Agentic Systems Explained
Tim explores the computational differences between single and multiple LLMs, highlighting the intriguing properties of agent architectures. Jeff emphasizes the importance of diversity in feedback, likening it to the peer review process for writing. He suggests that leveraging a variety of agentic systems could enhance the quality of outputs by incorporating diverse perspectives and expertise.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Jeff Clune - Agent AI Needs Darwin
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