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- Category: Prompts & Cie
Artificial intelligence (AI) has stepped firmly into the spotlight in recent years. Technologies like large language models (LLMs) - computer programs trained on vast datasets of text - can now hold surprisingly human-like conversations. Few developments have captured the public imagination so intensely since the dawn of the computer age. Yet, the inner workings powering such intelligent responses remain murky to most casual users.
The truth is that eliciting the most pertinent, nuanced and helpful answers from AI systems involves an art in itself. The key lies in careful prompting - priming the model with an intentional orientation before posing complex questions. This process sets the stage for AI to tap into precisely therelevant areas of its extensive data banks.
Read more: The Art of Unlocking Your Digital Assistant’s Full Potential
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As large language models such as ChatGPT receive widespread attention, optimizing prompts to guide their responses is becoming an important area of focus. A recent paper by researchers at the Mohamed bin Zayed University of AI makes a significant contribution by outlining principles for more effective prompting based on extensive experimentation. In this article, I would like to briefly review their work and offer some perspectives on the implications of their proposed best practices for prompt engineering. I appreciate the rigor and thoroughness underlying the formulation of these principles for eliciting better model performance.
My intention is not to position myself as an expert, but rather to reflect as an interested observer on how these insights might improve human-AI interaction by making prompt programming more structured. The ability to access improved responses from existing models simply through prompt design holds great promise. By sharing prompts more judiciously as users, we can likely further unlock the utility of language models in an ethical way.
Read more: Teaching AI to listen: The Art of Prompt Engineering
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- Category: Prompts & Cie
You grab your morning cup of coffee as your mind races ahead to the day's writing tasks. The expected progress report. An overdue set of customer service guidelines to draft. And what about that humor article idea you've been thinking about? Your own human brainpower falters in the face of such a demanding workload. But increase your potential productivity by 10 or even 100 times by putting a state-of-the-art large language model (LLM) to work for you through skilled prompting.
"Prompting activates everything the model then produces," points out Scott Count, Ph.D., lead researcher at Anthropic, creators of the constitutional AI assistant Claude. "With the right prompting strategy, over 50% of prompts will reliably produce excellent LLM results." We break down the key facets of prompting to maximize results from mediocre to great.
The Power of Priming
Read more: Cracking the code on prompts: A Guide to Maximizing Your Large Language Model