The video uses the example of generating a pickup line for Bumble. While a zero-shot prompt would simply be "Write me a pickup line for Bumble," a few-shot prompt would include one or more examples of successful pickup lines to guide the AI's response. The specific examples of pickup lines are not provided in the transcript.
This video summarizes Jeff Su's experience with Google's AI Essentials course. He shares five key takeaways, discusses the course's pros and cons, and assesses the value of the certificate received upon completion.
Chain-of-Thought prompting involves breaking down a complex task into smaller, more manageable steps. This helps the large language model produce more accurate and consistent results. The video uses writing a cover letter as an example. Instead of simply asking the AI to write a complete cover letter, Chain-of-Thought prompting would involve first asking the AI to generate an attention-grabbing hook based on the resume and job description, then using that hook to generate the body paragraph, and finally the closing paragraph. Each step builds upon the previous one, guiding the AI to a more coherent and well-structured final product.
The video gives two examples of surfacing implied context:
Restaurant Recommendations: A vegetarian friend asking for restaurant recommendations. The implied context is that the recommendations should be vegetarian-friendly, even if not explicitly stated.
Salary Negotiation: Preparing to negotiate a raise. The implied context includes past salary increases, current performance, and industry averages, which should be explicitly stated to the AI to get a better negotiation strategy.