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Rise of the Self-Driven Machine: Inside the World of Agentic AI
Abstract
AI refers to ability of machines to perform tasks that typically require human mind to perform such as learning, problem solving and decision making an agentic AI has been considered in large category. These systems depend on AI agents with purpose of independent entities that are capable of recognizing environment, learning & then performing the processes in multiple steps of workflow. Agentic AI accommodates LLM-based veracity. Through this classification strategy, AI agents are having the ability to seek real time data on fly and keep evolving with changes in world around them in sectors including healthcare, cybersecurity, logistics & personal services. In this chapter, we explore recent advancement in Agentic AI by analysing architecture, capabilities and real-world application of multi agent systems. These systems integrate LLMs to enable self-reliant decision making & task performing. We cover key methods such as retrieval–augmented generation, chain of thought promoting, increase learning with human feedback. It highlights how Agentic AI helps a machine to become autonomous.
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