AI Temperature: The Hidden Setting That Controls Research Quality
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AI Temperature: The Hidden Setting That Controls Research Quality
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Are you struggling to get reliable and repeatable results from AI in your professional research? This episode dives into the methodological rigour needed to turn large language models (LLMs) into trustworthy scholarly tools.
Join our discussion with R&D Engineer James Sutherland to uncover the secrets of advanced prompt engineering, including why giving your chatbot a "role" and demanding reasoning drastically improves accuracy. We explore the critical concept of AI "temperature" (and how it affects deterministic results) and connect it to the crucial academic field of uncertainty quantification. Learn how to build a multi-dimensional approach to AI analysis, moving beyond the simple "answer" to a complete, explainable methodology essential for AI standards and regulation.
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