Designing AI Evals: Clarity Now and Visualization Next
AI evals and analysis Let's say you're testing out new AI tools. Perhaps you implement and run analytics for an Ad Agency and hope to automate deploying your standard event schema, or are a podcast producer automating generating social copy from your newest ep. While modern, newly trained LLMs can likely one-shot a lot of these tasks – this specificity might necessitate wasting tokens and time…
When evaluating the performance of new AI tools, it is important to design objective measurements and collect relevant metrics. One way to achieve this is by using open source evaluation frameworks such as Inspect AI and Harbor. These frameworks allow you to assess agent skills and collect data on their effectiveness. However, designing effective evaluations and collecting useful metrics can be challenging.
To address this issue, this series will demonstrate how to create more objective evaluations of AI tools and how to use visualizations to identify trends and explore alternative approaches using tools like Google Sheets and Data Studio. By following along, you can gain a deeper understanding of how to evaluate AI tools and make informed decisions about their implementation.
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