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Semantic diffusion, dilution, and drift are endemic in tech because terms are so frequently co-opted by opportunists who want to find a way to sell the concept as a product.

What is interesting is that the first sentence is undermined by the second sentence, which is fairly reasonable compared to the first.

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I think there's a pedagogical component too. The way that things are taught have an outsized impact in how people think things are done. This extends far beyond concepts.

For example, and I've been guilty of this too, in data science, it's common for tutorials and examples to be use ipython/jupyter notebooks. This, however, should not be mistaken for "It's a good idea to use notebooks as part of the code-to-production pipeline." It's an easy mistake to make, and implicitly part of how AI/ML is taught.

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