Labelbox leaderboards: Redefining AI evaluation with private, transparent, and human-centric assessments

Labelbox has introduced a new approach to AI evaluation with their Labelbox leaderboards, addressing the limitations of traditional benchmarks and existing leaderboards, such as benchmark contamination and lack of scalability. These leaderboards utilize a scientific process and expert human evaluations to rank multimodal AI models, including image, speech, and video generation, with a focus on real-world applicability and resistance to data contamination. The comprehensive evaluation methodology incorporates sophisticated metrics like Elo and TrueSkill ratings, providing insights into model performance and allowing for continuous updates to reflect the latest advancements. By emphasizing expert judgment and transparency, the Labelbox leaderboards aim to offer a more nuanced and reliable assessment of AI capabilities, encouraging a shift towards more meaningful, human-aligned progress in AI development.