Imagine turning text like "A cat meows, then a dog barks" into realistic audio. Or even generating the perfect soundtrack directly from a silent video clip. That's the power of Audio-Agent, a groundbreaking AI framework that seamlessly blends text, video, and audio. Traditional methods for generating audio from text (text-to-audio, or TTA) often struggle with complex descriptions. They tend to create audio in one go, which can lead to a jumbled mess when the text describes multiple sounds. Audio-Agent solves this by using GPT-4 to break down complex instructions into smaller, manageable steps. For instance, "A car door opens, then closes, followed by the engine starting" becomes three separate audio clips that are intelligently combined. This allows for detailed control and far more realistic soundscapes. But Audio-Agent goes even further. It tackles the challenging task of generating audio from video (video-to-audio, or VTA), something that has largely remained unexplored. It uses a clever technique of converting video content into semantic tokens, which represent the essence of the visual information. These tokens help guide the AI to generate audio that is not only realistic but also perfectly synchronized with the video's action. This is a major step forward compared to traditional VTA methods, which often rely on complex and time-consuming synchronization processes. While the technology is still under development, Audio-Agent shows impressive results, outperforming existing methods on many tasks. However, handling exceptionally long or complex text descriptions can still be a challenge. Imagine generating a full movie score based only on a script—an enticing goal for future research. Audio-Agent opens doors to a future where creating rich, engaging audio experiences is easier and more intuitive than ever. From simplifying video editing and automating sound effects creation, to composing music from simple descriptions, the possibilities are seemingly endless. The future of sound is intelligent.