Anyone using AI without a sound, validated and approved use case should be held accountable for their reckless use of finite resources for pointless purpose
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@mgleadow My issue with AI discourse is what is meant by AI?
For example, the Dijkstra and A* algorithms were "AI" when they were developed. They or a variant are arguably used in all route finding applications today.
Or, if I build a machine-learning model using population density, the centre-line track-model and historic rail passenger data to predict travel likelihood. It uses scaling, a Histogram Gradient Boosting regressor, cross-validation and so on. So feels AI. But is it wrong?
1/n
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@wnd yes, I should have been more precise in use of language. I was specifically referring to the generation of unreliable filler content through the regurgitation of hastily hoarded input without consideration to nuance.
The use of scientific approaches to definable problems with measurable outputs can indeed have legitimate use, but the misappropriation of the term AI to mean generated content has poisoned the well
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@mgleadow ever was it so. If you follow the history of "AI" it has a long history of being hyped snake-oil.
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@mgleadow maybe we need a better set of words?
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@wnd I was resistant to the co-opting of AI as a cynical marketing tool but it achieved critical mass so I try instead to be more precise about what I mean if I use it correctly
Which is very similar to when "the cloud" was slapped on everything so I talked about *aaS
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@mgleadow were still in the XaaS phase. It's just painful.
The problem with the AI schtick is that we're arguably at the third or fourth iteration of its super hype cycle. Each one different, each one inevitably under delivering but equally eventually finding some kind of less hyperbolic level. The then not be AI anymore.
O tempora! O mores!
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text/gemini