The recent rise of powerful large language models (LLMs) has revolutionized the field of natural language processing (NLP).
The performance of these generative models is largely dependent on users’ prompts, which are becoming increasingly detailed and complex.
A Google Trends search reveals a hundredfold increase in popularity for the term “prompt engineering” over the last six months, and social media is teeming with novel prompting tips and templates.
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