Thread

1. Oras · 1789820747 · focus · HN ↗

   I played around with Jev last night and did it for classification tasks that I used Gemini 2.5 flash lite with.

   It’s a bit faster and bit cheaper, but this is compared to LLM. The consistency was nice to see, BUT, as someone who trained NLP models prior to LLMs, it’s just BERT with more data. I can see why people would want ready made one shot classifier, and I can see the value of sending multiple classifier in one call, but I wouldn’t call it breakthrough. And I believe many labs will replicate it in no time and might have it as part of their harness.

   I see it as a wake up call for the tech community to go back to basics for most tasks instead of relying solely on generic LLMs.

   1. tchalla · 1789823087 · focus · HN ↗

      Anyone who has worked in ML for 10+ years would already know that the usage of LLMs for everything is lazy, wasteful and a high degree of marketing on it.

      1. Oras · 1789824008 · focus · HN ↗

         I wouldn’t say lazy, LLMs are fast to use and much more cost effective especially if you factor the cost and time of training (data preparation, data cleaning, … etc).

         It’s hard to justify several months to business when there is something off-shelf ready to use and doesn’t require domain specialists to run.

         1. speq · 1789836748 · focus · HN ↗

            In other words, the "Bitter Lesson" (the famous essay)?

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