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Building the first LLM-based search engine for developers with Michael Royzen
High Agency: The Podcast for AI Builders
Start with Certainty: Generate Questions from Answers
Fine-tuning models rather than extensive prompt engineering can effectively enhance their performance. A strategic approach involves focusing on known correct outputs, such as human-created code, to generate synthetic inputs. This method leverages the strength of current models in summarization, making it easier to transform confirmed results into accurate questions. Relying on this process reduces the risks associated with generating incorrect data and demonstrates that creating dataset prompts from established answers is generally more productive than attempting to formulate answers from uncertain questions.
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