
#180 - Ideogram v2, Imagen 3, AI in 2030, Agent Q, SB 1047
Last Week in AI
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Advancements in AI: From Language Models to Autonomy
This chapter explores the evolution of AI from traditional language models to more autonomous agents, emphasizing guided decision-making and self-assessment capabilities. It highlights innovative methodologies for agent training, including the use of state-space models and Monte Carlo tree search to enhance performance in various applications. Additionally, the chapter addresses the challenges of 'loss of plasticity' in continual learning, proposing strategies to maintain model effectiveness as task complexity increases.
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