CONCEPT
Cost Over Capability
Moore's most transferable analytical principle: capability determines what a technology can do, but <em>cost</em> determines who uses it — and in the economics of exponential scaling, the 'who' always matters more than the 'what.'
The AI discourse is overwhelmingly focused on capability: what the models can do, how they perform on benchmarks, whether they can reason. Moore's framework inverts this priority. The 1965 paper was not about what integrated circuits could do; it was about what they would cost. Each transformative moment in the semiconductor industry was not when chips got faster but when they got cheaper — and each cost threshold crossed created categories of users that had never existed in the previous cost regime. Edo Segal reports that his Trivandrum team achieved a twenty-fold productivity multiplier at a cost of one hundred dollars per person per month; Moore's framework identifies the hundred-dollar figure, not the twenty-fold multiplier, as the more consequential number.
In The You On AI Field Guide
The Intel 4004, released in 1971, was the clearest illustration. Operating at 740 kilohertz and executing roughly sixty thousand instructions per second, it was by any capability measure inferior to the mainframes of the era.
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