Large language models and generative AI are extremely powerful because they allow us as humans to interact with AI tools in new ways we’ve never had before. But working with large language models, or LLMs, requires prompting. How we “design” our prompts – the order, the specificity, length, style, tone, and other aspects – are important to consider. We’ve led the teams that developed Prompt Builder and Einstein Studio, and we’ve gained critical learnings we’d love to share.
First, let’s define “prompts”: A prompt is what we call the message or “instructions” we submit to an LLM to be processed, thus giving us an answer or a “prompt response.” In natural language, we might say “question and answer.” When we refer to LLMs – deep-learning algorithms that perform a variety of natural language processing (NLP) tasks – it’s common to use “prompt and response” as the parallel terminology. Prompt
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