In this case, its people who have built BERT classifiers for years, pointing out you can just fine-tune some model to classify. Of course that's true, and still have value, but its not exactly turnkey. And Jev is surprisingly high quality at what its built for.

1 - https://news.ycombinator.com/item?id=9224

As William Gibson said, the future is already here, it’s just not evenly distributed.

So people get excited about existing technologies because they are new to them.

Wrapping an existing technology in a new package is a common way to introduce it to new people…there are many wrappers around ffmpeg, html2pdf, etc. that are marketed as products.

And they seem like magic…hell cassette tapes feel like magic to me even though I had a cassette player in 1973.

Often but not always, the best tool is the one in your hand or the one you know of because then you can just get to the work you are trying to do.

First make it work, then make it good. Good luck.

BeRT, BART and FLAN-T5, for text classification. All of those models are ~half a decade old now, are based on the transformer model, and small enough to run locally. They're not perfectly SOTA, but perform quite well in embedded applications. Fine for low-stakes stuff, I think.

Image classifiers are a hugely competitive space. You've got BeiT, DeiT, MobileOne, ConvNext, FastViT and several more models that all support image classification pipelines.