Advancing AI Reasoning: Exploring Self-Reflection and Self-Attention in Large Language Models

In this presentation, we explore the evolving landscape of AI reasoning through the lens of Large Language Models (LLMs). We will dive into how self-attention mechanisms enable LLMs to process and generate coherent responses, while introducing the concept of self-reflection in AI agents, allowing them to evaluate and refine their own outputs. By understanding these processes, we can better grasp the potential and challenges in developing more advanced, autonomous AI systems capable of complex reasoning.