Research
120d agoEvaluations Become The New Compute Bottleneck
Evaluating large models now requires massive compute resources, often rivaling the cost of training. Hugging Face notes that static benchmarks fail as models memorize test sets. This creates a critical need for dynamic, human-in-the-loop evaluation frameworks.
The Signal
Practitioners must now budget for rigorous testing to avoid deploying unreliable models.