Large Language Models like Gemma 2 and multimodal models such as Sora, Gemini, and LLaVA are advancing rapidly in AI research, offering improved performance in various tasks like text-to-video generation and multimodal comprehension. These models are designed to handle complex tasks by leveraging large-scale training on diverse datasets. The emergence of Large Language Models challenges traditional notions of intelligence and consciousness, sparking philosophical debates on the potential for machine consciousness to rival biological cognition. Despite their impressive capabilities, the inner workings of Large Language Models remain somewhat of a black box due to the complex nature of neural networks, raising questions about explainability and the nature of AI.