[2503.06378] General Scales Unlock AI Evaluation with Explanatory and Predictive Power

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a summary:Ensuring the safe and effective use of Amnesty International requires an understanding and expectation of its performance in new tasks, from advanced scientific challenges to the activities of the workplace. So far, the measurement has directed the progress of artificial intelligence, but it has provided a limited illustrative and impressive force for the artificial intelligence systems for general purposes, given the decrease in transportation through various tasks. In this paper, we offer general measures to evaluate artificial intelligence that can explain common standards to really measuring artificial intelligence, extracting cookies ability to artificial intelligence systems, predicting their performance of new mission situations, and distribution. Our entire methodology depends on 18 newly made models models that put an example of uncommon general standards. It is clear from 15 large linguistic model and 63 tasks. The high illustrative force is launched from the examination of the definition files and ability, which raises visions about the sensitivity and privacy that different criteria show, and how knowledge, knowledge and logic are affected by the size of the model, chain chain and mitigation. Surprisingly, high -level predictive power is possible to use these demand levels, which provides outstanding estimates on the foundation of black boxes based on domestic implications or transfers, especially in external distribution settings (new tasks and new standards). The standards, growths, battery, techniques and results submitted here are a major step to assess artificial intelligence, and support reliable publishing of artificial intelligence in the coming years. (Cooperative platform: URL https.)