Fluidity Index: Next-Generation Super-intelligence Benchmarks

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.