Fluidity Index: Next-Generation Super-intelligence Benchmarks
Eric Ngoiya, Tianshu Bao

TL;DR
The paper proposes the Fluidity Index (FI), a new benchmark to evaluate model adaptability in dynamic environments, emphasizing the importance of second-order adaptability for super-intelligence.
Contribution
It introduces the Fluidity Index (FI) as a novel metric and benchmark for assessing model adaptability and fluidity in evolving, scaling environments.
Findings
FI effectively measures response accuracy in changing environments
Distinguishes between closed-ended and open-ended benchmarks
Highlights the importance of second-order adaptability for super-intelligence
Abstract
This paper introduces the Fluidity Index (FI) to quantify model adaptability in dynamic, scaling environments. The benchmark evaluates response accuracy based on deviations in initial, current, and future environment states, assessing context switching and continuity. We distinguish between closed-ended and open-ended benchmarks, prioritizing closed-loop open-ended real-world benchmarks to test adaptability. The approach measures a model's ability to understand, predict, and adjust to state changes in scaling environments. A truly super-intelligent model should exhibit at least second-order adaptability, enabling self-sustained computation through digital replenishment for optimal fluidity.
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Taxonomy
TopicsGenerative Adversarial Networks and Image Synthesis · Anomaly Detection Techniques and Applications · Domain Adaptation and Few-Shot Learning
