EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Lobsters·Jul 28·5 min read
The mean means nothing
TL;DR
Visualizing performance data through cumulative distribution functions (CDFs) can reveal insights that traditional metrics overlook. This approach helps in understanding variability in benchmarks and production performance.
✦ Why It Matters
Start using cumulative distribution functions to analyze your performance data for deeper insights today.
Key Takeaways
- Always analyze multiple percentiles, not just the mean.
- Use CDFs to visualize data distributions effectively.
- Identify distinct populations in your data for actionable insights.
- Consider the impact of cache size on performance metrics.
How It Works
Cumulative distribution functions (CDFs) plot the fraction of requests that fall below a certain latency, allowing for a comprehensive view of performance across all percentiles. This method reveals shifts in latency distributions that single statistics cannot capture.