Improving Reproducibility of Gen AI Evaluations
Would you trust results that you can’t reproduce? Reproducibility is the backbone of trust in AI research. Without it, we risk misleading conclusions, wasted effort, and barriers to meaningful innovation.
💡Final thought: Improving reproducibility isn’t just about following best practices—it’s about building trust in the results we share and ensuring that our work stands the test of time.
In my last post, I shared why I believe learning NLP is a smart investment—even as generative AI takes center stage.
Today, I wanted to share my three favorite resources to learn NLP.
If you're interested in building evaluations for generative AI applications, I highly recommend this blog post by Hamel Husain: Creating a LLM-as-a-Judge That Drives Business Results hamel.dev/blog/posts/llm-jud…
Here are a few reasons why: