Undoubtedly, ChatGPT has marked a significant moment in the history of the internet. Personally, I was overwhelmed with emotions (I’m a writer, so I’m allowed to feel emotional about this) at the time of its release, realizing that it would revolutionize the way content is produced on the web.
Yet, I also couldn’t help but recognize the immense benefits of having a digital assistant that can comprehend human language.
The “best” (It’s been five months since release, and I’m still reeling…) part is that this is only the beginning of what artificial intelligence can achieve. Although access to GPT-4 and Plugins is still limited, people are already working on a plethora of projects that utilize AI technology, including ChatGPT.
As we continue to push the boundaries of what AI can accomplish, it’s clear that we’re living in a transitional period that will change the internet’s usage forever. Even though it feels like we’ve only taken the first step of an ultramarathon, we’re witnessing the dawn of a new era that will reshape the digital landscape.
So, what exactly is this page about?
ChatGPT can do a lot of things, you just have to ask
The basic premise of ChatGPT is the use of prompts to get answers.
You ask, “What color is the sky?”, and ChatGPT tells you, “It’s blue.”. You ask, “Can you rewrite the Still D.R.E song as if it was written by Eminem?”, and ChatGPT tells you, “It’s the E to the M-I-N-E-M.”.
A prompt can be as little as a few words, or it can be uniquely tailored and refined to try and maximize the potential for ChatGPT to give a satisfactory answer.
Personally, for projects that I have done over the last couple of months – I’ve had prompts that are sometimes 300 words long. This is also known as prompt engineering. You will get the best results when you actually sit down and put in the work to not only generate answers but also understand what could be improved about the answers you get.
As a display of commitment to this project, I’m starting things off with 20 categories that I believe are currently the most popular among ChatGPT users.
At this time, there are roughly 350 prompts across all of the categories, each categorized into unique sections and sub-sections.
Are you developing (or know someone who is) a product that can integrate OpenAI into external products? I am actively looking for solutions in various categories, as that will help me write more detailed guides on prompts, but also general use cases. Let me know by contacting me.
One thing you will note about the individual pages above is that they are almost exclusively focused on their individual category. But what if you are looking for more specific examples of using prompts? Well, I thought it would be useful to prepare some materials on this also.
What is prompt engineering?
Prompt engineering is the process of designing and optimizing prompts to elicit specific responses or behaviors from an AI language model, like ChatGPT. It involves carefully crafting input text in a way that effectively communicates the desired task or question, and often includes providing context, clarifying the intent, or specifying the format of the desired answer.
Prompt engineering is important because the quality of the AI’s output often depends on how well the input is designed. By refining the prompts, you can significantly improve the model’s performance, making it more useful and accurate in generating relevant and coherent responses.
Some strategies used in prompt engineering include:
- Experimenting with different phrasings or formulations of the same question or task.
- Providing explicit instructions or examples of the desired output.
- Setting context or constraints for the response, such as limiting the answer to a specific time period or domain of knowledge.
As AI models like ChatGPT become more advanced, prompt engineering plays an increasingly crucial role in leveraging their full potential and ensuring they provide meaningful and useful responses.
A thing that is important to understand about ChatGPT is that it can do more than just answer questions. This model has several NLP (natural language processing) capabilities, which means that it can also process the text that you give it. This also means that you can “chain” several requests, much like you would use a programming language. If ChatGPT can do sentiment analysis, then why not automate that, thanks to its code-generation capabilities? The possibilities, in many ways, are limited by your own interests.
It doesn’t matter that Plugins (Web browsing for ChatGPT) are coming. The fundamentals of designing prompts and understanding how to give instructions will remain the same (until the models get really good, of course). Simply by adding “step-by-step” at the end of a prompt can make a world of difference in the quality of output that you get!
All your questions about ChatGPT & OpenAI, answered
The section below is dedicated to answering common questions people have about both ChatGPT and OpenAI, the company that develops the GPT model.
Over time, these answers will grow richer as I integrate many of them into separate pages.
E.g. Learning how the GPT model works on a technical level, etc,.