Current AI benchmarks are struggling to maintain pace with modern models. As helpful as they’re to measure model performance on specific tasks, it could possibly be hard to know if models trained on web data are literally solving problems or simply remembering answers they’ve already seen. As models reach closer to 100% on certain benchmarks, additionally they develop into less effective at revealing meaningful performance differences. We proceed to speculate in recent and tougher benchmarks, but on the trail to general intelligence, we’d like to proceed to look for brand spanking new ways to guage. The newer shift towards dynamic, human-judged testing solves these problems with memorization and saturation, but in turn, creates recent difficulties stemming from the inherent subjectivity of human preferences.
While we proceed to evolve and pursue current AI benchmarks, we’re also consistently seeking to test recent approaches to evaluating models. That’s why today, we’re introducing the Kaggle Game Arena: a brand new, public AI benchmarking platform where AI models compete head-to-head in strategic games, providing a verifiable, and dynamic measure of their capabilities.
