TECH Signal 243
Four Time Scales for Technology Development and Deployment
Engineers building or adopting new tools regularly face pressure driven by hype cycles rather than proven research; understanding which time scale a technology occupies prevents overcommitting to something still years from reliable deployment. The historical examples given (neural networks taking roughly sixty years from initial models to LLMs, Linux taking over twenty years from creation to Microsoft adoption) set realistic expectations for adoption timelines.
Written by elseif from the cluster below · every claim links back to a sourceThe three things worth knowing
Solid research ideas typically require ten to twenty years before they reach convincing lab demonstrations, and some—like neural networks—took roughly sixty years of intermittent progress to reach today's LLMs.
Hype cycles frequently inflate expectations far beyond what a technology can currently deliver, and the ratio of extraordinary hype events to actual extraordinary technologies is far too high.
Even software with zero marginal cost generally takes twenty years or more to reach mass adoption, and hardware-based systems take even longer.
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