Abstract

Recent advancements in Large Language Models (LLMs), intelligent agents, and robotics have significantly impacted various industries and everyday life. The integration of AI and Machine Learning (ML) has accelerated these developments, with LLMs playing a crucial role in natural language processing, content generation, and autonomous agents. State-of-the-art models such as GPT-4 and LLaMA have enabled the creation of sophisticated applications, setting the stage for increasingly complex AI systems. Future trajectories involve refining LLM architectures to balance computational efficiency with enhanced functionality.

This short review highlights AI advances such as intelligent agents and robotics which are evolving towards proactive human interaction, utilizing LLMs to manage complex language-related tasks. Novel methods like Chain of Thought (CoT), self-reflection and ReAct extend LLM capabilities, enabling effective task decomposition and iterative improvements. In robotics, LLMs enhance command-based interaction, bridging language and action. Recent research shows high success rates in task completion, indicating potential for applications in home assistance, customer service, and medical settings.

Keywords:Large language models; Autonomous agents; Intelligent robotics; Chain of thought; LLMdriven robotics