The definition of 'better' is context-specific, emphasizing that different models serve different purposes; for example, one model may excel in question writing while another in fact retrieval. The utility of tools should be assessed based on real-world usefulness rather than performance in narrow benchmarks or competitions. Forecasting methods should prioritize their applicability to end users rather than just scoring well in tournaments. The aggregated wisdom of crowds can provide accurate future predictions, suggesting a need for broader adoption of this approach, which highlights that usefulness is a more significant measure than mere accuracy.

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