With all the present hype about generative AI and AI in general, it is worth considering that important new technologies that become widely adopted often take quite a long time to reach “ubiquity.”
And artificial intelligence is the poster child for expected major technology that has taken many decades to reach “awareness,” and is only in the early stages of “adoption.” Granted, there are very high hopes for applied use cases, such as generative AI.
Some might point to the Eliza chatbot, created in 1966, as a starting point. Assuming we can say that generative AI is entering the early phases of adoption, then Eliza, a rule-based system that could simulate human conversation, represents a 57-year gestation.
To the extent that generative AI is a form of neural network, and if we date neural network research to the early 1980s, with a working prototype created in 1987, then generative AI has been in development for 36 years.
To the extent that generative AI is an application of generative adversarial networks in 2014, then generative AI to support use cases such as Image, text, music, video generation; gaming or drug discovery might be said to have been nearly a decade in the making.
And while AI has been an unusually slow developing capability, even lots of other innovations have taken decades to reach ubiquitous use.
With the caveat that we can argue about when “adoption” first happened, it can easily take a decade before any important and valuable new technology is generally used by four out of five people. “Decades” is not an unusual length of time before that happens.
AI is important, most of us agree. But the commercial fruit will take some time to ripen.
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