Agentic Systems Evolution
The conversation delves into the development of agentic systems, which are complex workflows that enhance the capabilities of language models. By moving beyond simple queries, these systems integrate tools and methods to produce more refined results. Emphasizing the shift from hand-designed systems to learned pipelines, the discussion highlights the potential of utilizing open-endedness and quality diversity algorithms to create increasingly sophisticated AI systems.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Jeff Clune - Agent AI Needs Darwin
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