In this episode of the DataFramed podcast, AI expert Alex Banks dives into the topic of prompt engineering. He shares key strategies for creating effective prompts for ChatGPT, emphasizing the need for clarity, specificity, and open-ended questions. Banks introduces the Persona Problem Solution Framework and highlights the importance of refining prompts through iteration and evaluating responses with the LAF criteria: Logical Consistency, Accuracy, Relevance, and Factual Correctness. He also explores challenges such as model biases and "hallucinations," offering strategies to address these issues. Ultimately, Banks underscores the rising significance of prompt engineering, suggesting it could develop into a distinct career path.
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