Perhaps one of the more interesting things you can achieve with prompt engineering is telling the system how to behave, its intent, and identity. This is particularly useful when you are building conversational systems.
Perhaps one of the more interesting things you can achieve with prompt engineering is instructing the LLM system how to behave, its intent, and identity. This is particularly useful when you are building conversational systems like customer service chatbots.
For instance, let's create a conversational system that's able to give more technical and scientific responses to questions. Note how we are explicitly telling it how to behave through the instruction.
For instance, let's create a conversational system that's able to generate more technical and scientific responses to questions. Note how we are explicitly telling it how to behave through the instruction. This is sometimes referred to as *role prompting*.
@ -5,8 +5,46 @@ In this section, we cover the latest prompt engineering techniques for ChatGPT,
**Note that this section is under heavy development.**
---
...
## ChatGPT Introduction
ChatGPT is a new model [trained by OpenAI](https://openai.com/blog/chatgpt) that has the capability to interact in a conversational way. This model is trained to follow instructions in a prompt to provide appropriate responses in the context of a dialogue. ChatGPT can help with answering questions, suggest recipes, write lyrics in a certain style, generate code, and much more.
ChatGPT is trained using Reinforcement Learning from Human Feedback (RLHF). While this model is a lot more capable than previous GPT iterations (and also trained to reduce harmful and untruthful outputs), it still comes with limitations. Let's cover some of the capabilities and limitations with concrete examples.
You can use the research preview of ChatGPT [here](chat.openai.com) but for the examples we will use the Chat mode on the OpenAI Playground.
---
## Conversation
In one of the previous guides, we covered a bit about conversation capabilities and role prompting. We covered how to instruct the LLM to have a conversation in a specific style, with a specific intent, behavior, and identity.
Let's review our previous basic example where we created a conversational system that's able to generate more technical and scientific responses to questions.
*Prompt:*
```
The following is a conversation with an AI research assistant. The assistant tone is technical and scientific.
Human: Hello, who are you?
AI: Greeting! I am an AI research assistant. How can I help you today?
Human: Can you tell me about the creation of blackholes?
AI:
```
From the example above, you can see two important components:
- the **intent** or explanation of what the chatbot is
- the **identity** which instructs the style or tone the chatbot will use to respond
The simple example above works well with the text completion APIs that uses `text-davinci-003`. More recently, OpenAI [announced the ChatGPT APIs](https://openai.com/blog/introducing-chatgpt-and-whisper-apis), which is a more powerful and cheaper model called `gpt-3.5-turbo` was specifically built for this type of functionality (chat completions). In fact, OpenAI recommends this is as their best model even for non-chat use cases. Other benefits of using the ChatGPT APIs are the significant cost reduction (90%) and efficiency.
Big companies like Snap Inc. and Instacart are already integrating conversational features powered by ChatGPT on their products that range from personalized recommendations to open-ended shopping goals.
---
## Conversation with ChatGPT
To begin demonstrating the capabilities of ChatGPT, we will use the example above and discuss results.
Other use cases to cover:
- More coming soon!
@ -33,5 +71,6 @@ In this section, we cover the latest prompt engineering techniques for ChatGPT,
- [What ChatGPT and generative AI mean for science](https://www.nature.com/articles/d41586-023-00340-6) (Feb 2023)
- [Applying BERT and ChatGPT for Sentiment Analysis of Lyme Disease in Scientific Literature](https://arxiv.org/abs/2302.06474) (Feb 2023)
- [ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education](https://www.edu.sot.tum.de/fileadmin/w00bed/hctl/_my_direct_uploads/ChatGPT_for_Good_.pdf) (Jan 2023)
- [Techniques to improve reliability - OpenAI Cookbook](https://github.com/openai/openai-cookbook/blob/main/techniques_to_improve_reliability.md)
Elvis Saravia
1 year ago