Short videos are everywhere, but so is misinformation. How can we tell the real from the fake? Researchers are exploring the power of AI and Large Language Models (LLMs) to detect misleading content in videos. A new framework called VMID tackles this challenge by combining the strengths of LLMs with multimodal analysis. This means it doesn't just look at the words being said, but also analyzes the audio, visuals, and even metadata like comments and likes. VMID breaks down the video into keyframes, transcribes the audio using a tool like Whisper, and uses models like CogVLM2 to understand the visual content. All this information is then combined into a single prompt and fed to a fine-tuned LLM. The LLM acts like a detective, piecing together the clues from different modalities to determine whether the video is spreading misinformation or debunking it. Initial tests are promising. VMID outperformed existing methods on a dataset of fake news videos, achieving a high accuracy rate. However, like any detective, AI isn't perfect. The model sometimes struggled with subtle cues, like sarcasm or complex visual manipulations. The research highlights the potential of LLMs and multimodal analysis in the fight against misinformation. Imagine a future where AI can fact-check videos in real-time, helping us navigate the increasingly complex online world. This technology is still under development, but it offers a glimmer of hope in the battle against fake news.