Fundamental principles of creating effective prompts

📌 The course covers the fundamentals of creating effective prompts and best practices.

🧩 Two fundamental principles for prompt creation are clear and specific instructions and giving the model time to think.

📝 Practical tactics include delimiting prompts with quotation marks and requesting structured outputs.

📝 Using the tactic of asking the model to confirm if conditions are met can help verify if the model understood the request correctly.

🧩 By providing specific instructions, the chat GPT model can generate steps based on the given text.

❓ Asking the model to confirm if conditions are met is a useful tactic to reduce the risk of receiving an incorrect response.

The tactic of offering an example of the expected result helps the language model understand what is expected.

Providing examples in a consistent style helps produce accurate and relevant responses.

Using alternative options in explanations can enhance understanding and engagement.

📝 Writing clear and specific instructions is the first key principle in creating effective prompts.

⏳ Giving the model time to think is the second key principle, and it can be done by specifying the steps to complete a task and asking the model to work on its own solution.

💡 Providing examples and downloadable programs for practice is recommended throughout the course.

🔑 The video discusses the importance of verifying equation results before providing an answer.

📝 Two best practices for creating effective prompts are evaluating and modifying the response to obtain accurate results, and summarizing the prompt in different ways.

💡 Different types of summaries, such as summary, compendium, and extract, yield varying results and should be chosen based on specific needs.

🔑 Prompt engineering involves the use of good practices to improve prompts and achieve desired outcomes.

🔍 Inference is the process of using available information to draw conclusions, and in the context of chat GPT, it helps analyze a text's main theme, tone, purpose, target audience, and historical/social context.

💡 A practical example of the use of inference is extracting and analyzing reviews of a product from Amazon to determine the general sentiment, positive and negative opinions, main advantages, and main disadvantages.

📝 Creating effective prompts using the copy-paste method on Amazon reviews in chat gpt.

👍 Positive sentiment and advantages of an economical temporary repair solution, while acknowledging the glue's potential loss of effectiveness and some users' desire for cutting guides.

💡 Impressive ability of chat gpt to infer information from Amazon reviews, utilizing techniques learned in the course to generate useful results.