Large language models like GPT-3 have demonstrated impressive text-generation abilities. Now, researchers are working to develop similarly capable large vision models for image understanding. This episode explores how visual prompts train these models to interpret and generate images. We discuss different types of visual prompts, the benefits of flexible prompts over fixed ones, and innovations like prompt tuning.
Key examples covered include CLIP, SAM, and DALL-E. We examine challenges like performance degradation in complex scenarios. The episode shares insights from a new research paper reviewing progress in large vision models and prompt engineering. You can tune in to learn how visual prompts provide critical guidance to teach nuanced visual intelligence skills to machines.