The recent advancements in the field of Large Language Models (LLMs) and Vision-Language Models (VLMs) have shown significant progress in integrating ethical considerations, enhancing video understanding capabilities, and improving computational efficiency. A notable trend is the development of models that exhibit emergent 'moral minds', capable of consistent ethical reasoning across diverse scenarios. This development is crucial as LLMs are increasingly integrated into decision-making processes across various sectors. Another key area of innovation is in video processing, where models like Espresso and LinVT have introduced novel methods for spatial and temporal compression, enabling better understanding of long-form videos and transforming image-based LLMs into video-LLMs respectively. Safety and cultural sensitivity have also been addressed with the introduction of benchmarks like SafeWorld, which evaluates LLMs' ability to generate culturally sensitive and legally compliant responses across diverse global contexts. Additionally, models like SafeWatch and Granite Guardian have been developed to ensure safety and security in video generation and LLM interactions, providing transparent explanations and comprehensive risk detection. The field is also seeing advancements in streaming video interaction with models like StreamChat, which updates visual context dynamically during decoding. Overall, these developments indicate a shift towards more ethical, efficient, and culturally aware AI systems.