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Advancements in AI Training and Decision-Making
This chapter explores the evolution of continuous training and online learning in AI, focusing on shorter update cycles and real-time adjustments driven by user feedback. It also discusses the limitations of current neural networks and the need for reliable agentic architectures, while emphasizing the integration of various AI technologies and the importance of clean data. Furthermore, it highlights the future challenges of developing AI systems capable of true decision-making and understanding user intent.