No matter which AI tool you choose to use, the quality of the answer is dependent on the quality of the prompt. Using the CLEAR (Concise Logical, Explicit, Adaptive, and Reflective) framework by Leo S. Lo as a guide will help you think critically about your prompts to generate useful AI responses.
Focus on keeping your prompt short and clear. When you leave out unnecessary details, it helps the AI focus on the important parts of your prompt which can lead to better and more accurate results. Using vague of confusing prompts an cause the AI to give you a response that isn't useful.
| Poor | "My instructor wants me to write a paper about a book we read in class. It's called First Gen: A Memoir. Can you suggest some topics I could write about? The paper needs to be 10 pages long, so make sure they're really good topics." |
| Better | "Suggest topics for First Gen: A Memoir for a class writing assignment." |
Keep your prompts organizes and easy to follow. When your ideas are in a clear, logical order, the AI can better understand how everything fits together. This helps it give you more accurate and focused responses. To do this, make sure your prompt flows naturally and shows how the different ideas are connected.
| Poor | "What should you include in a group presentation, and how do you divide the work after you start creating slides?" |
| Better | "Describe how to plan a successful group presentation, beginning with assigning roles and ending with practicing as a team before presenting." |
Be specific about what you want. When you clearly ask the AI what kind of answer you need such as how long it should be, what it should include, or what format should it follow, its more likely to give you a helpful and accurate response. Be sure to include details about what kind of information you are looking for and how you want to present it.
| Poor | "Tell me about photosynthesis." |
| Better | "Give a brief explanation of photosynthesis suitable for a biology exam review, including the main steps and the role of sunlight." |
Make sure your prompts are flexible! Sometimes ask your questions in different ways. This could mean changing how you word things and shaping the response to fit the specific task that you are working on. Try to be open to trying new approaches based on how well the AI is responding.
| Initial Prompt | "What are some ways to conserve water?" |
| Adaptive Prompt | “List three water-saving habits a student could use in a dorm room and explain how each helps reduce waste. |
Take time to reflect on how your prompts are working. By thinking about what went well and what could be better, you can improve the way you ask the AI for help. Making reflection a regular habit helps you get better results and keep up with changes in how AI works. Always review the responses and use what you learned to make stronger prompts.
| Initial Prompt | “Give strategies for managing time.” |
| Reflection | The suggestions were basic and didn’t consider a student’s schedule. |
| Improved Prompt | “List five time management strategies tailored for full-time college students balancing work and school.” |
Lo, L. (2023). The clear path: A framework for enhancing information literacy through prompt engineering. The Journal of Academic Librarianship, 49 (4), Author’s last name(s), https://doi.org/10.1016/j.acalib.2023.102720.
Prompt Engineering for Generative AI
by
Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation. With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice. When first integrating LLMs and diffusion models into their workflows, most developers struggle to coax reliable enough results from them to use in automated systems. Authors James Phoenix and Mike Taylor show you how a set of principles called prompt engineering can enable you to work effectively with AI. Learn how to empower AI to work for you. This book explains: The structure of the interaction chain of your program's AI model and the fine-grained steps in between How AI model requests arise from transforming the application problem into a document completion problem in the model training domain The influence of LLM and diffusion model architecture--and how to best interact with it How these principles apply in practice in the domains of natural language processing, text and image generation, and code
Transformers for Natural Language Processing
by
OpenAI's GPT-3, ChatGPT, GPT-4 and Hugging Face transformers for language tasks in one book. Get a taste of the future of transformers, including computer vision tasks and code writing and assistance.Purchase of the print or Kindle book includes a free eBook in PDF format Key Features Improve your productivity with OpenAI's ChatGPT and GPT-4 from prompt engineering to creating and analyzing machine learning models Pretrain a BERT-based model from scratch using Hugging Face Fine-tune powerful transformer models, including OpenAI's GPT-3, to learn the logic of your data Book Description Transformers are...well...transforming the world of AI. There are many platforms and models out there, but which ones best suit your needs?Transformers for Natural Language Processing, 2nd Edition, guides you through the world of transformers, highlighting the strengths of different models and platforms, while teaching you the problem-solving skills you need to tackle model weaknesses.You'll use Hugging Face to pretrain a RoBERTa model from scratch, from building the dataset to defining the data collator to training the model.If you're looking to fine-tune a pretrained model, including GPT-3, then Transformers for Natural Language Processing, 2nd Edition, shows you how with step-by-step guides.The book investigates machine translations, speech-to-text, text-to-speech, question-answering, and many more NLP tasks. It provides techniques to solve hard language problems and may even help with fake news anxiety (read chapter 13 for more details).You'll see how cutting-edge platforms, such as OpenAI, have taken transformers beyond language into computer vision tasks and code creation using DALL-E 2, ChatGPT, and GPT-4.By the end of this book, you'll know how transformers work and how to implement them and resolve issues like an AI detective. What you will learn Discover new techniques to investigate complex language problems Compare and contrast the results of GPT-3 against T5, GPT-2, and BERT-based transformers Carry out sentiment analysis, text summarization, casual speech analysis, machine translations, and more using TensorFlow, PyTorch, and GPT-3 Find out how ViT and CLIP label images (including blurry ones!) and create images from a sentence using DALL-E Learn the mechanics of advanced prompt engineering for ChatGPT and GPT-4 Who this book is for If you want to learn about and apply transformers to your natural language (and image) data, this book is for you.You'll need a good understanding of Python and deep learning and a basic understanding of NLP to benefit most from this book. Many platforms covered in this book provide interactive user interfaces, which allow readers with a general interest in NLP and AI to follow several chapters. And don't worry if you get stuck or have questions; this book gives you direct access to our AI/ML community to help guide you on your transformers journey! ]]>
Getting Started With ChatGPT And AI Chatbots
by
Learn how to use ChatGPT, Bing Chat / Copilot, and Gemini (Bard) to get the most out of these powerful tools. ChatGPT has become a tool hundreds of millions use every day - yet few have mastered the art of sweet-talking these new AI chatbots into providing detailed and accurate responses to user prompts. It's vital for every professional tech user to have an understanding of how AI chatbots work, and how best to put them to work. While the fear is that AI will take people's jobs, it is more likely to be someone using AI that will! Getting Started with ChatGPT and AI Chatbotsexplores the 'big three' AI chatbots - OpenAI ChatGPT, Microsoft / Windows Copilot and Google Gemini (Bard) - demystifying their operation, and providing a wealth of tools for thinking about how to talk to these smart tools. Whether you're a business user, a tech student, or a curious professional, this book is for you to understand and demystify Large Language Models (LLMs) and generative AI tools, harnessing them to enhance your role.
