The Fine Art of Talking to AI, Unraveling ChatGPT's Prompt Processes for End Users

Welcome to "Exploring AI with ChatGPT". This is the second post in the series after launching two weeks ago with our introductory post. For the purpose of helping you understand what this blog series is and what we are trying to achieve with it, we'll first explain the function and purpose of "Exploring AI with ChatGPT". We don't this in every post going forward, but for the purposes of this first true edition of the blog, it is probably worth explaining in case you didn't read the intro.

What is "Exploring AI with ChatGPT"?

"Exploring AI with ChatGPT" is a new bi-weekly blog post from Mark Jones . "Exploring AI with ChatGPT" explores key topics relating to the usage of Generative AI by the means of conducting "interviews" with ChatGPT.

Going forward, the blogs will be made up of three key parts:

• Explaining the topic at a high-level.
• Conducting the "interview" with ChatGPT.
• ChatGPT's top tips surrounding the topic.

The content provided during the course of these interviews should provide readers with some good insights on what Generative AI is and what it is capable of.

In terms of a target audience, this blog is designed to be applicable to users of Generative AI at all levels. However, much of the prompts I will give to ChatGPT over the course of my interviews will be designed to provide information that users with little to no experience of ChatGPT can understand. In terms, of why I've specifically chosen to use ChatGPT, that is quite simple actually. The reason for using ChatGPT is because out of the main available options or what we'll be doing, ChatGPT is the tool that is probably the most widely used. That being said, much of what we will be covering will be applicable to likes of Google Bard as well.

That should provide enough of an introduction to the blog, so let's get into the topic for today's post. This post will be looking at the topic of Prompt Engineering.

Introducing the Topic of Prompt Engineering

Prompt engineering forms the bedrock of the usage of tools like ChatGPT. Prompt engineering is the process of crafting requests to Generative AI tools in the hope of AI generating a response that matches the desired outcome of the request.

This is how Wikipedia describes Prompt Engineering:

Prompt engineering is the process of structuring text that can be interpreted and understood by a generative AI model. A prompt is natural language text describing the task that an AI should perform.

Prompts are essentially made up of ingredients with these ingredients being markers that the Generative AI tool uses in order to formulate the response it provides. Over the course of this post, you will get a bit of an overview into Prompt Engineering and how ChatGPT in particular produces responses to your prompts.

With that introduction now being said, let's go to my "interview" with ChatGPT.

My Interview with ChatGPT and Its Responses

To help formulate this post, I "sat down" with ChatGPT and asked it several questions on the subject of Prompt Engineering. Below you will find each of the questions I asked along with the response from ChatGPT. Let's get into it.

What is Prompt Engineering and What Are It's Key Components?

My Question: "For users who may be new to Prompt Engineering and Generative AI tools such as yourself. Can you briefly explain in a single paragraph what Prompt Engineering is at a high level. If there are any key items that make up a prompt can you outline that in a list describing each item. Keep your answer understandable to all users if at all possible."

ChatGPT's Response:

Prompt Engineering is the practice of crafting inputs (prompts) to effectively communicate with generative AI models, like ChatGPT, to achieve desired outputs. This process involves understanding how these models interpret and respond to language, and thus tailoring the prompts to guide the model towards generating specific, accurate, and relevant responses.

Key elements of a prompt include:

1. Clarity of Intent: Clearly stating what you want the AI to do. This could be answering a question, writing a story, or generating a piece of code.

2. Specificity: Providing enough detail to guide the AI's response. More specific prompts lead to more accurate and targeted outputs.

3. Context: Including relevant background information or setting, which helps the AI understand the scenario or subject matter more deeply.

4. Tone and Style: Indicating the desired tone (e.g., formal, casual) or style (e.g., professional, humorous) of the response.

5. Constraints and Guidelines: Setting boundaries or rules for the response, such as word count limits or avoiding certain topics.

6. Examples (Optional): Sometimes providing an example or template for the desired output can be helpful, especially for complex tasks.

By mastering these elements, users can more effectively communicate with AI models and harness their capabilities for a wide range of applications.

What Happens a User Provides ChatGPT with a Prompt

My Question: "OK great. Now that you've outlined what a prompt is. Can you explain what happens when a user provides you with a prompt. I understand that this will vary depending on the prompt, but what I am wanting you to explain is at a high-level what you do when a user provides you with a request via a prompt."

ChatGPT's Response:

When a user provides me with a prompt, a high-level process is initiated to generate a response. Here's an overview of what happens:

1. Receiving the Prompt: First, I receive and interpret the prompt. This involves understanding the language, the intent behind the words, and any specific instructions or requirements mentioned.

2. Contextual Understanding: I analyse the prompt in the context of my training. This includes recognising the topic, the style or tone requested, and any specific details or constraints. My training involves a vast database of text, allowing me to understand and respond to a wide range of topics.

3. Response Generation: Based on the prompt and my training, I generate a response. This process involves selecting relevant information and constructing sentences that align with the prompt's requirements. My goal is to create a coherent, relevant, and accurate response.

4. Adhering to Guidelines: Throughout this process, I adhere to ethical guidelines and content policies. This means avoiding harmful, inappropriate, or biased content and respecting user privacy.

5. Delivering the Response: Finally, I present the response to the user. The response aims to be clear, informative, and as closely aligned with the user's intent as possible.

This process happens rapidly, often in a matter of seconds, allowing for a fluid and interactive experience with the user. The sophistication of the response depends on the complexity of the prompt and the nuances of the request.

How Does ChatGPT Adhere to Ethical Guidelines

My Question: "That's great, thank you. Before we move on, I'd like you to unpack point 4 on "Adhering to Guidelines" a little bit more. We'll be talking about the ethics of AI in a future post. But for now, can you provide a little more insight on how you adhere to ethical guidelines and content policies."

ChatGPT's Response:

Adhering to ethical guidelines and content policies is a crucial aspect of my operation. Here's how I ensure compliance with these standards:

1. Content Filters: I am equipped with filters that automatically screen for and prevent responses that could be harmful, offensive, or inappropriate. This includes avoiding hate speech, explicit content, and promoting unsafe activities.

2. Bias Mitigation: My design and training include measures to minimise biases. While no AI system is entirely free from bias, efforts are made to ensure responses are fair, balanced, and do not perpetuate harmful stereotypes or inaccuracies.

3. Respecting Privacy: I am programmed to not store personal data shared during interactions and to avoid requests that involve personal data processing, ensuring user privacy and data protection.

4. Adherence to Legal and Ethical Norms: My responses are aligned with legal and ethical norms, which means avoiding involvement in illegal activities or offering legal, medical, or other professional advice that I'm not qualified to give.

5. User Safety: I prioritise user safety, both online and offline, by not encouraging or supporting dangerous behaviour and by providing responses that are intended to be constructive and safe.

6. Continuous Monitoring and Improvement: My performance and adherence to these guidelines are continuously monitored. Feedback mechanisms are in place to improve and update these guidelines, ensuring they remain relevant and effective.

Through these measures, I strive to provide helpful, respectful, and ethically aligned interactions with all users.

How Does ChatGPT Handle Vague Prompts

My Question: "That's great, thank you. Now, one of the things that commonly happens unfortunately, is that you will be provided with vague prompts. Can you speak a little on how the provision of vague prompts can impact the strength and accuracy of your responses? Why is it important for a user to provide you with a prompt that is clear and detailed?"

ChatGPT's Response:

When dealing with vague prompts, there are several challenges and implications for the strength and accuracy of my responses:

1. Ambiguity: Vague prompts often lack specific details, making it challenging to determine the user's exact intent. This can lead to responses that are generic or off-target because I have to make assumptions about what the user might be asking.

2. Broad Interpretation: Without clear guidance, I might interpret the prompt in multiple ways, leading to a response that covers a broader range than what the user intended. This can result in less relevant or overly general answers.

3. Quality of Information: The specificity and clarity of a prompt directly influence the quality of the information provided in the response. A well-defined prompt allows me to generate more accurate, detailed, and tailored information.

4. Efficiency: Clear and detailed prompts enable more efficient interactions. Users are more likely to get the information or output they need on the first try, reducing the need for follow-up questions or clarifications.

5. Utilising AI Capabilities: Detailed prompts better leverage my capabilities. They allow users to guide the response more precisely, making the most of the AI's potential to generate creative, insightful, or highly specific content.

For these reasons, it's important for users to provide clear and detailed prompts. Doing so improves the interaction quality, ensures more accurate and relevant responses, and enhances the overall user experience with AI tools like ChatGPT.

What About the Training Data for the Free Version of ChatGPT?

My Question: "OK great. That's helpful, thank you. Following on from that, it is widely known that you are trained on a large volume of data in order to provide your responses. Can you provide some insight on that area? Can you tell us the limitations of the training data (such as when the training data goes up to date-wise) for the free version of ChatGPT?"

ChatGPT's Response:

Certainly! My responses are based on the extensive training data I've been provided, which includes a wide range of texts from books, websites, and other written sources. Here are some key insights and limitations regarding my training data:

1. Training Data Cut-Off: My training includes data up to April 2023. This means that any events, developments, or information that emerged after this date are not within my knowledge base. For instance, I wouldn't be aware of recent news, scientific discoveries, or cultural developments that occurred post-April 2023.

2. Broad Scope: The training data encompasses a vast array of subjects, languages, and styles, which allows me to respond to a wide range of queries. However, the breadth of this data also means that the depth of knowledge in certain specialised or niche areas might be limited.

3. Bias and Representation: Despite efforts to minimise bias, the training data is not free from the biases inherent in human-generated text. This can affect the neutrality and perspective of my responses. Moreover, the representation of certain topics or groups might reflect the biases or imbalances present in the source materials.

4. Accuracy and Reliability: While I strive for accuracy, I don't have the ability to verify the current accuracy of my training data against real-world changes or recent research. Hence, some information might be outdated or superseded by new findings.

5. Generalisation vs. Personalisation: My responses are based on generalised knowledge and are not personalised to individual users. I don't have access to personal data about users unless shared with me in conversation, and I am designed to forget this information after the conversation ends to ensure privacy.

Understanding these limitations is important for users to set realistic expectations about the responses they receive and to approach them with a critical mindset, especially for topics that are rapidly evolving or highly specialised.

How Do the Free and Premium Versions Compare in this Area?

My Question: "Great, thank you. Now, how does that compare with ChatGPT that uses either a premium version or is integrated into something Bing for Microsoft Edge?"

ChatGPT's Response:

The premium versions of ChatGPT or integrations like ChatGPT in Bing for Microsoft Edge may offer certain enhancements compared to the free version, but the core functionality and training data are fundamentally similar. Here's a comparison:

1. Training Data: Both the free and premium versions of ChatGPT, as well as the Bing integration, are based on the same core model trained on data up to April 2023. This means that the knowledge base and the limitations related to the cut-off date for training data are similar across these versions.

2. Response Speed and Capacity: Premium versions often offer faster response times and higher capacity, meaning they can handle more users simultaneously without significant slowdowns or queueing.

3. Advanced Features: Premium versions or integrations like Bing might include advanced features. For instance, Bing's integration of ChatGPT could offer a more seamless browsing experience, allowing users to interact with the AI in the context of web searches, potentially providing more current information by pulling from recent online sources.

4. Customisations and Updates: Premium versions may receive more frequent updates or have customisations that are not available in the free version. These could include enhanced understanding of certain domains, improved interaction capabilities, or interface enhancements.

5. Access to Information: Integrations like Bing for Microsoft Edge might have direct access to current web content, which can provide more up-to-date information, especially for queries about recent events or trending topics.

Overall, while the foundational AI model and its capabilities remain consistent, premium versions and specific integrations like Bing for Microsoft Edge offer enhanced user experiences, faster interactions, and potentially more current information through direct web integration.

How Does ChatGPT Learn from Interactions With its Users?

My Question: "OK. That's good to know. Let's now move on to how you learn from interactions. Do you learn from the chats that users have with you? If so, how do you apply that learning to future prompts? And does that knowledge apply to just interactions with that user, or does it apply to all users of the product?"

ChatGPT's Response:

My learning process is not quite the same as real-time learning from each interaction. Instead, it's structured and managed through periodic updates and training cycles. Here’s how it works:

1. Learning from Interactions: I don't learn or retain information from individual chat interactions in real-time. Each conversation is independent, and I don't have the ability to remember personal data or previous interactions for future use, ensuring user privacy.

2. Data Analysis and Model Training: The way I learn is through analysis of large sets of data and subsequent model retraining. OpenAI, the organisation behind ChatGPT, periodically reviews interactions (in an anonymised and aggregated form) to identify patterns, common queries, and areas for improvement.

3. Model Updates: Based on these analyses, my underlying model may be updated. This involves retraining on a new dataset that includes these insights, which helps improve accuracy, reduce biases, and enhance overall performance. These updates apply globally, meaning the improvements are not specific to interactions with any single user but rather are incorporated into the model that all users interact with.

4. Continuous Improvement: This process of analysis, retraining, and updating is ongoing, ensuring that the AI model evolves and improves over time. However, these improvements are implemented in a controlled manner to maintain consistent performance and quality standards across all interactions.

In summary, while I don't learn or adapt during individual interactions, the collective insights gained from user interactions contribute to periodic improvements and updates to the AI model, benefiting all users.

What Improvements Can We Expect Regarding Prompt Reading?

My Question: "OK, so as we begin to wrap up. Let's talk about your point about "Continuous Improvement". Is there anything the readers of this blog should be aware of around this topic? How can we expect to see ChatGPT improve in the future when it comes to understand a user's prompt and the context behind it?"

ChatGPT's Response:

The concept of "Continuous Improvement" in the context of ChatGPT is pivotal, and there are several aspects that readers should be aware of:

1. Model Training and Updates: The most significant improvements come from periodic retraining of the AI model. This involves incorporating new data, refining algorithms, and addressing identified weaknesses. Future versions of ChatGPT will likely have a more extensive training dataset, including more recent information, and improved algorithms to understand and process prompts more effectively.

2. Better Context Understanding: Future iterations of ChatGPT are expected to have enhanced abilities in understanding context and nuance in prompts. This means the AI will be better at interpreting the underlying intent, managing ambiguous or complex requests, and providing more accurate, relevant responses.

3. Reduced Bias and More Balanced Responses: Ongoing efforts are being made to reduce biases in AI responses. This involves both improving the training data to represent a wider range of perspectives and refining the model to handle sensitive topics more appropriately.

4. Increased Personalisation: While respecting user privacy and data security, future versions might offer more personalised interactions by temporarily remembering context within a single session. This would allow for more coherent and connected conversations, especially in longer interactions.

5. Enhanced Interactivity and Capabilities: Future developments may include better interactive features, like understanding and generating more complex content (e.g., sophisticated code, creative stories), and more seamless integration with other tools and platforms.

6. User Feedback Role: User feedback plays a critical role in continuous improvement. Feedback on responses, reporting issues, and providing suggestions help guide the development and training priorities for future updates.

7. Ethical and Responsible AI Use: As capabilities evolve, there will be an ongoing focus on ethical AI development. This includes ensuring AI is used responsibly, maintaining user privacy, and aligning with societal norms and values.

In conclusion, ChatGPT is expected to evolve with richer understanding, more nuanced responses, and broader capabilities, all while adhering to high standards of ethical AI practice. Users can look forward to an increasingly sophisticated tool that better understands and responds to their needs and prompts.

ChatGPT's Top Three Prompt Engineering Tips

To close out this post, here are ChatGPT's top three tips on the subject of Prompt Engineering. These tips are ChatGPT's top three pieces of advice to help you as a User craft the highest quality prompt in order to receive the best quality response.

1. Be Specific and Detailed:

- Description: Clearly define what you're asking for. Include specific details relevant to your request. The more precise your prompt, the more targeted and accurate my response can be. For example, if you're asking for a summary, specify the length; if it's a technical query, mention the context or specific requirements.

- Benefit: This reduces ambiguity and guides the AI to the exact type of response you're seeking.

2. Provide Context:

- Description: Context is crucial. It frames your prompt and helps me understand the background and the scope of your question or request. For example, if you're asking about a historical event, mentioning the relevant time period or key figures can significantly improve the response's accuracy and relevance.

- Benefit: With adequate context, I can tailor my response more effectively to fit the specific scenario or topic you're inquiring about.

3. Use Clear and Concise Language:

- Description: While detail is important, clarity and conciseness are equally so. Avoid overly complex sentences or jargon that might confuse the AI. Clear and straightforward language helps in formulating a coherent and on-point response.

- Benefit: This ensures that the AI correctly interprets your prompt and focuses on the core aspects of your request, leading to a more precise answer.