Improving a Financial Analysis Prompt
A junior financial analyst uses a language model to help understand a company's quarterly performance. The analyst provides the model with the full text of the company's latest earnings report and the following instruction: "Analyze this earnings report and identify the main risks for investors."
The model produces a generic list of risks, such as "increased market competition" and "potential economic downturns," without referencing any specific data from the report.
Analyze why the initial instruction failed to produce a useful, data-driven response. Then, describe three distinct pieces of information or context the analyst could add to their instruction to guide the model toward a more specific and insightful analysis grounded in the provided report.
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Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
Related
A marketing manager is using a language model to generate social media posts for a new product: a reusable water bottle made from recycled ocean plastic. The manager's initial prompt is: "Write three social media posts for a new reusable water bottle." The generated posts are very generic and lack impact. Which of the following revised prompts most effectively incorporates relevant prior knowledge to produce more compelling and targeted marketing content?
Improving a Financial Analysis Prompt
Enhancing a Prompt for Urban Planning