Editing Research:Question-18-AI-Capability-Prediction (section)

=== Performance Gap Convergence ===

Analysis reveals significant convergence in AI model performance across different scales and architectures. The performance gap between leading models has narrowed substantially, from 11.9% difference in key benchmarks in 2023 to 5.4% in 2024. This convergence suggests that fundamental scaling approaches are reaching similar effectiveness levels, with implications for future competitive dynamics and prediction accuracy.

The convergence pattern appears most pronounced in [[Natural Language Processing]] tasks, while maintaining greater variation in reasoning-intensive and multimodal applications. This differential convergence provides insights into which capabilities may be more predictable versus those subject to breakthrough-driven advancement.