AI improvement at the labs has evolved from a guessing game to one driven by precision-targeted fixes to identified failure modes. @scale_AI's SEAL research benchmarks and evaluation platform is making this possible. Check out coverage by @willknight https://t.co/lB3V6ozU7A
Check out the work @danielxberrios and @scale_AI have been doing to help AI labs evaluate model performance! https://t.co/yoECLNKBP6
Today we're announcing updates to Scale Evaluation platform to help AI labs better evaluate their models' performance ✅instant model comparison ✅multi-dimensional performance visualization ✅automated error discovery ✅targeted improvement guidance
Scale AI has announced updates to its Scale Evaluation platform, aimed at enhancing the evaluation of artificial intelligence models. The new features include instant model comparison, multi-dimensional performance visualization, automated error discovery, and targeted improvement guidance. This initiative is part of a broader effort to assist AI developers in identifying weaknesses in their models, moving the process from a trial-and-error approach to one based on precise, targeted fixes. The updates are expected to facilitate better performance assessments across various modalities, including language, speech, video, image, and code. Industry experts have noted the importance of such benchmarks in determining model superiority.