Capability Growth vs. Public Narrative
To understand how rapidly modern technology, especially Artificial Intelligence, is changing our world, we must look at two major forces: the physical limits of computing power and the patterns in how society adopts new ideas.
The observation that transistor counts on microchips double approximately every two years, resulting in exponential computing growth.
A major transition from agrarian and manual production toward machine-centered industrial production.
A recurring pattern in which technological excitement overshoots reality before settling into practical value.
The pace of technological change is often driven by predictable physical trends. One key example is , which explains why computing capability can compound over time rather than improve only in isolated jumps.
This exponential growth mirrors historical shifts such as the , which fundamentally reorganized production, labor, and the structure of economic life.
However, public understanding rarely tracks capability growth cleanly. The explains why media and investment narratives often swing from overclaim to disappointment before settling into a more durable understanding.
This distinction matters for AI: hardware and model capabilities can improve on a relatively steady curve, while expectations, fear, and market interpretation move in bursts. A careful learner should keep those two rhythms separate.
