Prompt Engineering (PE)
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- Prompt Engineering (PE) ...PromptBase ... Prompt Injection Attack
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- Few Shot Learning
- Prompt Engineer | Anthropic ... Salary - The expected salary range for this position is $175k - $335k
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- Lists:
- Best practices for prompt engineering with OpenAI API | OpenAI
- Prompt Engineering Guide | Elvis Saravia - dair.ai ... lecture, notebook, & slides
- ChatGPT cheatsheet | QuickRef.ME
- Learn Prompting ... a Free, Open Source Course on Communicating with Artificial Intelligence
- 12 ways to get better at using ChatGPT: Comprehensive prompt guide | Aaron Mok - Insider
Prompt is the starting point for a model to generate output; a language model to generate text, providing context for text generation in natural-language-processing tasks such as chatbots and question-answering systems, or an application to generate images.
Contents
What is Prompt Engineering (PE)?
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Prompting for Text vs Image Generation
Prompting for text generation and image generation are two different tasks, and as such, the prompts that are used for each task are also different.
- For text generation, the prompt is typically a short sentence or phrase that describes the desired output. For example, a prompt for generating a poem might be "A sonnet about love." The prompt should be specific enough to give the model a clear idea of what is desired, but it should also be open-ended enough to allow for creativity.
- For image generation, the prompt is typically a more detailed description of the desired image. This might include the subject of the image, the setting, the mood, and any other relevant details. For example, a prompt for generating an image of a cat sitting on a chair might be "A realistic image of a black cat sitting on a red chair in a sunny room." The prompt should be as detailed as possible to give the model a clear idea of what is desired.
Here are some tips for writing effective prompts for text generation and image generation:
- Be specific. The more specific the prompt, the better the model will be able to understand what you are asking for.
- Be open-ended. Don't be afraid to leave some room for creativity. The model will use its knowledge of the world to fill in the blanks.
- Use keywords. If you are not sure how to describe something, use keywords that are related to it. For example, if you want to generate an image of a cat, you could use the keywords "cat," "animal," "furry," and "meow."
- Use examples. If you can, provide examples of the kind of output you are looking for. This will help the model to understand what you are trying to achieve.
Text Generation Prompting
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- Requirements Management ... Generative AI for Business Analysis
- The Art of ChatGPT Prompting: A Guide to Crafting Clear and Effective Prompts | Faith Akin ...free e-book
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Advice from ChatGPT
Human-Machine Interaction (HMI) is used in engineering for asking questions or interacting with an artificial intelligence like myself is often referred to as Human-Computer Interaction (HCI) or Human-Machine Interaction (HMI). These terms describe the study and practice of designing, evaluating, and implementing interactive systems or devices that allow humans to communicate with machines, including artificial intelligence models like myself. This can involve designing user interfaces, voice and Speech Recognition, Natural Language Processing (NLP), and other technologies that allow people to communicate effectively with machines. In general, engineers and designers in the field of HCI/HMI are focused on creating systems and devices that are intuitive, user-friendly, and effective at facilitating communication between humans and machines, like me, to achieve certain goals. As an AI language model, I am designed to assist you with your questions and concerns. Here are some tips on how to ask and converse with me effectively:
- Be clear and specific: Clearly state your question or topic of conversation. The more specific you are, the better I can understand and provide a relevant response. For example, instead of asking "Tell me about cars," you could ask, "What are some popular electric car models available in the market today?"
- Use simple language: While I can understand complex language, using simple and straightforward language helps ensure clear communication. Avoid unnecessary jargon or complex sentence structures.
- Provide context: When asking a question, provide any relevant context or background information. This helps me better understand your needs and provide a more accurate response. For example, if you're asking about the best places to visit in a city, let me know your interests or preferences, such as whether you enjoy historical sites, outdoor activities, or cultural experiences.
- Use examples: If you're looking for specific information or examples, providing examples can help clarify your question or illustrate what you're seeking. For instance, if you want advice on writing a cover letter, you could provide a sample sentence or paragraph from your draft and ask for suggestions for improvement.
- Assign me a specific role: If you want me to provide information or act as a specific role, such as a travel agent, historian, or creative writer, let me know. This helps me understand the context and provide responses accordingly.
- Let me know the reading level: If you have a preference for the reading level of the response, such as basic, intermediate, or advanced, please specify. This allows me to adjust the complexity of the language used in the response to match your preference.
- Ask for an outline: If you have a lengthy question or want a comprehensive answer, you can request an outline of the main points first. This allows you to review the structure of the response and ask me to elaborate on specific sections.
- Follow up with additional questions: Feel free to ask follow-up questions to seek further clarification or delve deeper into a topic. This helps me understand your needs better and provide more detailed and relevant information.
- Be patient: While I strive to generate responses quickly, complex queries may require a bit more time for processing. Please be patient and allow me a moment to generate a thoughtful and accurate response.
Remember, I am a language model designed to assist you, so feel free to ask any questions or have any conversations you would like. I'm always here to help!
Image Generation Prompting
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- DALL-E
- Stable Diffusion
- MidJourney
- CLIP Interrogator ... Want to figure out what a good prompt might be to create new images like an existing one?
- ArtBreeder ... a collaborative, machine learning-based art website. Using the models StyleGAN and BigGAN
- Here’s a Whole Bunch of Sites to Help You With Image Prompts | Daniel Nest - Why Try AI:
- Lexica ... a massive database of images generated via Stable Diffusion, with prompts attached. You can search the library, explore styles related to a selected image, and easily copy text prompts to use elsewhere. You can even generate images directly on the site.
- PromptHero ... not limited to just Stable Diffusion, organizes images into a few top-level categories like “Anime,” “Architecture,” “Landscapes,” etc. making it easier to browse images related to the same theme.]
- Prompt Hunt ... filter by your preferred AI art generator
- Prompt builders -
- Prompter ... use Midjourney, prompt builder, Google Sheet that lets you customize all possible aspects of your Midjourney prompt.
- promptoMANIA ... all-in-one prompt builder; guides you through picking your subject, styles, artist tags, and other relevant descriptors. You also get nice visual references for the modifiers, giving you a decent idea of how your final image might turn out.
- Automated prompt generators -
- Stable Diffusion Prompt Generator ... demo of the model series: “MagicPrompt”
- Midjourney Prompt Generator generates multiple prompts which often include Midjourney-specific tags like “--ar” (to set the aspect ratio).
- AI Prompt Generator ... creates a narrative around your subject, describing the setting in great detail using natural language. You can then plop it into any text-to-image program.
- Image-to-text tools -
- CLIP Interrogator ... features a neat “Analyze” tab that breaks down your prompt into underlying components like “Artist,” “Medium,” etc.
- Img2Prompt by Methexis ... tweaked version of the CLIP Interrogator.
- PEZ Dispenser ... condense an existing text prompt into a shorter one
After I have a rough idea of what I want to accomplish, I try to narrow things down to people, places and things - the core actors or main drivers in the scene I’m trying to construct. I use the service to generate a few rough prompts to get a feel for what the scene might look like. I find it much easier to take something that works well and then add on to it rather than having to go back and remove things until it looks better. You start with the big important strokes and then work in the finer details.
... I see prompt writing from the perspective of an artist, coder and engineer. I use my programming experience to help me understand how the service may interpret my prompt, which guides me to more effective tinkering with it to coax the results I’m after. Every word in a prompt has a weight associated with it, so trying to work out what works best and where becomes a core asset in the skillset. My background in software quality assurance is a pretty big driver in that “what happens if” style of thinking. - Professional AI whisperers have launched a marketplace for DALL-E prompts | Justin Reckling interviewed by article author Adi Robertson - The Verge
Prompt Techniques
Recursively Criticizing and Improving the output (RCI)
The RCI approach significantly outperforms existing LLM methods for automating computer tasks and surpasses supervised learning (SL) and reinforcement learning (RL) approaches on the MiniWoB++ benchmark. RCI is competitive with the state-of-the-art SL+RL method, using only a handful of demonstrations per task rather than tens of thousands, and without a task-specific reward function. Furthermore, we demonstrate RCI prompting's effectiveness in enhancing LLMs' reasoning abilities on a suite of natural language reasoning tasks, outperforming Chain of Thought (CoT) prompting. We find that RCI combined with CoT performs better than either separately.
Chain of Thought (CoT) prompting
The process of an AI model using its own human tendency to ‘think out loud’ is called inner speech or self-dialog. Chain-of-Thought (CoT) prompting can dramatically improve the multi-step reasoning abilities of Large Language Model (LLM)s. CoT explicitly encourages the LLM to generate intermediate rationales for solving a problem, by providing a series of reasoning steps in the demonstrations. There are two main methods to elicit chain-of-thought reasoning: few-shot prompting and zero-shot prompting. The initial proposition of CoT prompting demonstrated few-shot prompting, wherein at least one example of a question paired with proper human-written CoT reasoning is prepended to the prompt. CoT prompting can effectively elicit complex multi-step reasoning from Large Language Models (LLMs).
However, it is not clear whether CoT is still effective on more recent instruction finetuned (IFT) LLMs such as ChatGPT. IFT is a method for improving the performance and usability of pretrained language models. It involves finetuning language models on a collection of datasets phrased as instructions, which has been shown to improve model performance and generalization to unseen tasks Surprisingly, on ChatGPT, CoT is no longer effective for certain tasks such as arithmetic reasoning while still keeping effective on other reasoning tasks. Moreover, on the former tasks, ChatGPT usually achieves the best performance and can generate CoT even without being instructed to do so.
Resources - Text Generation
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- Lists:
- Apps:
- WriteGPT | OpenAI ... web extension to facilitate prompt writing
- WebChatGPT ... qunash -GitHub ... A browser extension that augments your ChatGPT prompts with web results.
- YouTube & Article Summary powered by ChatGPT | Glasp
- Bottom right in subheader click on '...', 'Show Transcript', Above the transcript, click on 'Transcript & Summary'
Prompt Vine
- Prompt Vine ... a large collection of ChatGPT prompts, a community-driven library so that you can contribute to the dozens of categories
- PromptVine ChatGpt Prompts | Startup Ai Tools
Prompt Vine provides a variety of useful prompts to help you use ChatGPT and AI Chatbots effectively. You can find the best ChatGPT prompts by category, profession, or use case. In addition to ChatGPT prompts, it also provides Bing AI, GPT-3, Bard, and GPT-4 prompts to make your AI conversations more engaging.
PromptBase
- PromptBase ... Find top prompts, produce better results, save on API costs, sell your own prompts.
- The wild world of PromptBase, the eBay for Generative AI prompts | Ryan Broderick - Fast Company ... There’s an art to writing the string of prompts that can produce what you want from ChatGPT, DALL-E 2, and Midjourney. Right now, there are more buyers than sellers.
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writeGPT
- WriteGPT | OpenAI ... web extension to facilitate prompt writing
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Artificial Intelligence-Powered Response Manager (AIPRM)
- AIPRM
- AIPRM for ChatGPT | Google Web Store
The AIPRM extension adds easy to use list of curated prompt templates for ChatGPT curated for you by a community of prompt engineering experts. The long-awaited release with many free features, but also many new premium features like “Favorites”, “Hidden”, your own Custom Lists, Custom Writing Tones, Custom Writing Styles, (Custom) Power Continue actions. Now with Multiple Variables in the Prompt, support for everyone, also free users, as well as the long-awaited LIVE CRAWLING feature and the CLONE Private Prompt feature.