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Verisk’s evaluation involved three major parts: Promptengineering – Promptengineering is the process where you guide generative AI solutions to generate desired output. Verisk framed prompts using their in-house clinical experts’ knowledge on medical claims.
The platform incorporates the innovative Prompt Lab tool, specifically engineered to streamline promptengineering processes. Notably, the prompt text, model references, and promptengineering parameters are meticulously formatted as Python code within notebooks, allowing for seamless programmable interaction.
One of the hardest things about MLOps today is that a lot of data scientists aren’t native software engineers, but it may be possible to lower the bar to software engineering. How do you have a similar tool for experimentation on prompts? Keep track of versions of prompts and what worked and all that.
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