Prompt Engineering: The Magic Words to using OpenAI's CLIP

OpenAI's CLIP model is a versatile zero-shot image classifier that can identify image content based on text prompts without the need for specific dataset training. It excels in mapping text to images, which is crucial for tasks like sorting unlabeled images. To maximize CLIP's potential, developers engage in prompt engineering, crafting text prompts that best elicit the correct classifications from the model. Through a series of experiments involving the recognition of hand signs from rock, paper, scissors, it was demonstrated that prompt engineering involves trial and error to refine prompts for accuracy. Initial attempts using specific game-related prompts yielded moderate success, while revised prompts focusing on literal descriptions improved accuracy significantly. The process underscores the importance of iteration and precise language in prompt engineering, suggesting that literal prompts may be more effective and that including context like "a person" can influence the outcomes.