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Superhuman AI: Fine Tuning vs Prompt Engineering When There’s Lack of Data
The speaker discusses the challenge of training language models on email data due to the lack of quality training data. Despite this challenge, customers desire the AI to reflect their writing style. The speaker emphasizes avoiding fine tuning due to the time-consuming process of assembling and tagging data, and the inability to transfer it to updated models. Instead, they advocate for pushing the limits of prompt engineering to achieve personalized email responses and highlight the effectiveness of this approach in mimicking the user's writing style.