Jev framed as democratizing classifiers: no training, real-time, cheap
The author argues Jev is not a new concept but turns decades-old classifiers into a real-time decision layer anyone can use; custom classifiers will still win, but retail-grade is good enough.
Unlike LLMs, Jev didn't invent a new concept. Classifiers have existed for decades, with exactly the same interface → ask a question, get a probability score. BUT, here's what the hype is all about: - it works for *any* problem, no training required - it's fast → you can do stuff in real-time - it's cheap You can see it as a democratization of classifiers. Before, only those with a huge amount of their own training data could own one. Now, you get your own at the speed of thought. This won't disrupt the existing classifier market. Custom-trained classifiers will always beat the one-size-fits-all solution. But this opens a whole new market for the rest of us where retail is more than good enough. It's the same thing that happened with digital photography, Canva, 3d printing, and vibe coding.
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