ChatGPT-4 Shot Prompting

 

ChatGPT-4 Shot Prompting

The best prompts for ChatGPT incorporate relevant details to help the platform understand the specific scenario or context. That way, it can provide more accurate responses. Include information like background info, specific facts, or user preferences. ChatGPT offers spaces to fill in your information for “Product X.”

Shot Prompting

Use a few explicit examples (or shots) to guide the AI to respond in a specific way. This is called "Few Shot" prompting.Few-shot prompting can be used as a technique to enable in-context learning where we provide demonstrations in the prompt to steer the model to better performance. Few-shot learning refers to a machine learning paradigm where a model is trained to make accurate predictions with only a small number of examples per class. This approach enables the model to generalize well to new, unseen data despite having limited training data.

Few-shot prompting is helpful when you want a response to be structured in a specific wa

Few-Shot Prompting

If you cannot describe what you want but still want a language model to give you answers, you can provide some examples. It is easier to demonstrate this with the following example:

A conversation between Astrologer, the author of a jyotishgher Astrology, and a Client:

Client: Why should I learn about Prompt Engineering? Astrologer: Because Generative AI can really boost your productivity if used correctly, and knowing how to write prompts correctly is the key to helping you use generative AIs.
Student: What will I learn from this tutorial?
Client: This tutorial gives step-by-step guides on how to write AI prompts to get the best possible results from ChatGPT-3.5. You will learn to understand ChatGPT-4's capabilities and write prompts that minimize misinformation and biased results.

Client: That sounds interesting. Can you give me an example of how Prompt Engineering can be used in real-world applications?
Astrologer: Prompt Engineering can be used in a wide range of applications, such as content creation, customer service, and even scientific research. For example, let's say you're running a content creation platform and want to generate engaging article titles for your writers. Using Prompt Engineering techniques, you can write prompts that will help create article titles that are attention-grabbing and relevant to your readers. Another example is using generative AI to answer customer service inquiries. By writing well-crafted prompts, you can ensure that the AI responses are accurate and helpful, leading to higher customer satisfaction.

Here you can see that no instruction on what to do is provided, but with some examples, the model can figure out how to respond. Also, note that the model responds with “Neg” rather than “Negative” since it is what is provided in the examples.

Note: Due to the model’s random nature, you may be unable to reproduce the exact result. You may also find a different output produced each time you run the model.