Given the amount of hype around large language models, which seemingly has lots of firms deploying it at some level just to be seen as doing it, it won’t be long now before we start seeing lots of articles lamenting the fact that large language models are not producing results for firms that are using them.
No truly-important general purpose technology is going to produce clear results right away. And even technologies most observers would consider useful, but not GPTs, similarly take some time to reach as much as 10 percent use by the relevant potential-user base (people, homes, businesses).
Technology | Year of Introduction | Time to 10% Adoption (Years) | Notes |
Electricity | 1873 | 46 | Homes in US |
Telephone | 1876 | 39 | Households in US |
Automobile | 1886 | 51 | Individuals in US |
Radio | 1920 | 14 | Households in US |
Television | 1948 | 12 | Households in US |
Computer | 1975 | 23 | Households in US |
Internet | 1995 | 10 | Individuals in US |
Smartphone | 2007 | 6 | Individuals globally |
Social Media | 2004 | 7 | Individuals globally |
As was true during an earlier time for the internet, when many firms engaged in a mania to rename themselves X.com, there is lots of almost-blind posturing going on.
Large language models will be deployed where it does not make much sense, and where measurable results will be nil, if clear benefits exist at all.
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