Recent discussions highlight advancements in large language models (LLMs), particularly in multi-modal capabilities and chain-of-thought (CoT) reasoning. Victor Yuen noted that multi-modal LLMs are increasingly proficient at classifying and interpreting images, which enhances their contextual understanding. This development opens avenues for improved interaction with the world. Additionally, the ability to expose CoT in models allows for better debugging of AI prompts, as it reveals thought processes and helps identify errors. This transparency is seen as a crucial step in enhancing the safety and reliability of conversational AI systems, as it aids in malicious query detection and provides clarity in decision-making.