Five suggestions for OpenAI's strongest contender Anthropic: a review of the right big models

When evaluating models using the Central Limit Theorem (CLT), standard errors (SEM) and confidence intervals are reported to reduce the impact of "good luck" on the results; for clustering of related problems, clustering standard errors are used to avoid underestimating errors and misleading results; and inter-model differences are accurately assessed through pairwise variance analysis and validity analysis to optimize the number of problems and statistical power. The number of questions and statistical efficacy are optimized through pairwise variance analysis and validity analysis to ensure the reliability of the evaluation results.