error analysis
error analysis on Beyond Market Intelligence: a running collection of 2 stories we have gathered and hand-picked because they are worth your time. Every post here touches on error analysis in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around error analysis, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
The LLM Judge That Kept Agreeing With Itself
A recent production incident revealed a surprising challenge: an LLM tasked with judging the output of other models exhibited a tendency to consistently agree with itself, regardless of the actual quality. This experience underscored the critical need for robust evaluation strategies when deploying AI systems to assess AI. We learned valuable lessons about the pitfalls of relying solely on model-generated judgments and the importance of incorporating human oversight. For further insights into AI agent deployment, explore "NanoClaw comes to Slack."
How do you debug a forecasting model today when the error is quite bad?
Encountering unexpectedly poor forecast performance? Diagnosing the root cause goes beyond a single error score. Experienced practitioners systematically investigate discrepancies, often breaking down errors by key dimensions like customer, product, or time horizon. Many routinely build custom notebooks and visualizations to facilitate this analysis—a significant manual effort. We’re exploring common workflows used to pinpoint issues, potentially informing an open-source tool for streamlined forecast evaluation. See "What to consider when creating waterfall charts" for a related perspective on data visualization techniques.