Evaluating Models is Getting Even Harder

2026-07-14 · Source: The Information · Field: Technology & Digital — Artificial Intelligence & Machine Learning · Depth: Advanced, quick

Summary

Evaluating advanced AI models is becoming increasingly challenging, as researchers note models quickly saturate existing benchmarks, necessitating the rapid development of harder evaluations. A more subtle issue, highlighted at the International Conference on Machine Learning (ICML), is that today's models can work on tasks for hours or days, meaning their performance evaluation also takes a comparable amount of time. OpenAI researcher Noam Brown stated during an ICML panel that models could soon "work for weeks or indefinitely," particularly in fields like drug discovery. This extended operational time implies that evaluating a model might eventually take longer than its initial training, posing practical difficulties and potentially slowing down the overall model development process.

Key takeaway

For AI Scientists or Machine Learning Engineers developing advanced models, you must anticipate significantly longer evaluation cycles, potentially exceeding initial training times. As models operate for days or weeks on complex tasks like drug discovery, your project timelines and resource allocation need to factor in these extended validation periods. Proactively design evaluation strategies that scale with model complexity to prevent bottlenecks and maintain development velocity.

Key insights

Advanced AI models are increasingly difficult to evaluate due to benchmark saturation and extended task execution times.

Topics

• AI Evaluation
• Model Benchmarking
• Machine Learning
• AI Development
• Long-running Models
• Drug Discovery

Best for: Research Scientist, AI Product Manager, AI Scientist, Machine Learning Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by The Information.