The weekly token shifts from new AI model releases certainly give us a quick pulse on immediate interest, and it's valid concern to track how quickly demand can jump.
However, to truly understand a model's sustained intelligence and market value, we need to combine that immediate data with longer-term use, much like how a sudden fever indicates a problem, but a chronic condition requires observing symptoms over time for a proper diagnosis.
A workable middle ground means acknowledging the dynamic nature of early market turbulence while grounding our understanding in more robust, usage-weighted intelligence scores that reflect real-world, ongoing integration, not just passing curiosity—otherwise, we risk reacting to every cough as if it were pneumonia.