AI model evaluations are becoming a significant computational bottleneck, demanding more resources than model training.
Why it matters
As AI models become more sophisticated, the process of rigorously evaluating their performance, safety, and fairness is becoming increasingly resource-intensive. This 'evaluation bottleneck' can slow down the iteration cycle for AI development, making it harder and more expensive to deploy new models. Addressing this challenge is crucial for the continued progress and widespread adoption of AI technologies.
Testing AI models is becoming as hard and expensive as building them. This means it's taking longer and costing more to make sure AI works well and is safe.
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