dailyai.report

Evaluating large models now requires more resources than the training process itself. Hugging Face notes that static benchmarks fail as models memorize test sets. This creates a critical shortage of high-quality, dynamic evaluation data. Practitioners must shift toward human-in-the-loop verification to ensure model reliability as compute scales.