“Killer apps” often are important in spurring adoption of new technologies. It was the spreadsheet which drove financial personnel to buy and use personal computers. It was the ability to watch over-the-air television which drove early cable TV adoption in rural areas, while it was commercial-free Home Box Office which arguably drove urban area customers to buy.
Mobile email access drove adoption of the BlackBerry smartphone. The touchscreen interface arguably drove adoption of the iPhone and all subsequent smartphones. Turn-by-turn directions supplied by navigation apps such as Google Maps drove some mobile network and device upgrades.
And that has been typical for general purpose technologies: there is typically a particular use case that drives adoption.
Lighting is generally considered the first important use case for electricity. Pumping water from coal mines was the important early use case for steam engines, followed by its use to power textile machinery. Autos were the killer app for internal combustion engines.
It is less clear which apps drove consumer interest in the internet, though music sites such as Napster played a role.
But there were also several other contenders that drove interest in using the internet, including email, the multimedia web and web browsers; search engines and instant messaging. Electronic file sharing and e-commerce also were lead use cases.
Social media platform adoption reached about 10 percent use by the internet-connected population in the United States between 2005 and 2015, for example.
We will have to wait a while to identify the AI “killer app,” either for large language models or broader AI adoption in other ways, though personal assistants, entertainment, health and wellness, education or creative tools have been suggested as promising early use cases.
And some might suggest large language models and generative AI could eventually be seen as the killer app that spurred broader consumer use of AI. But beyond that, the issue is which implementations and use cases for LLM will drive obvious and broad consumer or entity value?
And at what cost?
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