🧩Explicit instructions provide more detail and specificity to improve chatbot responses.
💡Zero shot prompting allows chatbots to generate responses without previous examples.
🔗Fuse shot prompting combines role-based instructions with examples for more accurate and context-aware responses.
🔐Role prompting sets context and helps chatbots provide role-specific answers.
🔁Chain of thought prompting helps chatbots reason step-by-step to provide better responses.
What is zero shot prompting?
—Zero shot prompting allows chatbots to generate responses without any previous examples, relying solely on the specified prompt.
How does fuse shot prompting work?
—Fuse shot prompting combines role-based instructions and examples to guide chatbots in generating accurate and context-aware responses.
What is chain of thought prompting?
—Chain of thought prompting helps chatbots reason step-by-step to provide more accurate and logical responses.
How does self-consistency improve chatbot responses?
—Self-consistency prompts chatbots to generate multiple answers for the same question and choose the best one based on consensus.
What is retrieval augmented generation (RAG)?
—Retrieval augmented generation (RAG) prompts chatbots to use external sources for research and provide more up-to-date and factual answers.
00:00Introduction to 7 powerful prompting techniques for AI chatbots.
01:20Explanation of explicit instructions and the importance of providing specific prompts.
02:47Introduction to zero shot prompting, which allows chatbots to generate responses without previous examples.
04:45Explanation of fuse shot prompting, combining role-based instructions and examples for more accurate responses.
06:45Introduction to role prompting, setting context for chatbots and guiding role-specific answers.
09:15Explanation of chain of thought prompting, enabling chatbots to reason step-by-step for better responses.
10:45Introduction to self-consistency, prompting chatbots to generate multiple answers and choose the best one.
12:35Explanation of retrieval augmented generation (RAG), using external sources for research and more accurate answers.
