BYOB: Bring Your Own Benchmark

1. 1Identify the limitations of generic evaluations for AI systems
2. 2Create custom benchmarks tailored to your specific use case
3. 3Run experiments to compare your model's performance on generic vs custom benchmarks
4. 4Analyze the results to understand how your model behaves in production-like environments
5. 5Refine your model based on the insights gained from custom benchmarking

Data scientists and AI engineers can benefit from this knowledge to improve their model's performance in real-world scenarios

💡 Generic evaluations may not accurately reflect your AI system's performance in production, custom benchmarks are necessary

💡 Generic evals won't cut it! Create custom benchmarks to accurately predict your AI system's production behavior