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Ollaya – Ollama for open-source, Jev-style decision models

618 points · 145 comments · Ardakilic

  1. pradn · · focus · HN ↗
    I'm not sure what this means for AI startups if their innovations can be copied by OSS so quickly (what, like 2 weeks?). There's "consumer surplus" for everyone, to borrow an economic concept. But we do ideally want some of the surplus to flow to the innovator, too. I know there were precursors, but that's fine - it's hard to have a totally novel idea in such a popular field. I don't know what the end game is for TypeSafe - they'd need to demonstrate perpetually better results, or compete in another axis: UX, support, custom solutions, etc. So much of the time, someone proving a concept, or it simply getting enough publicity, is enough for a "Cambrian explosion" of follow-ups and copies. Famously, that was true for "Attention is All You Need", and the general idea of "next-token prediction" being so powerful.

    We've stumbled into general differentiable models..

    1. redox99 · · focus · HN ↗
      Because what they did is kinda trivial. Its basically like the Dropbox comment really[0], except here you don't need petabytes of storage and infinite VC pockets.

      After chatgpt everything in AI mostly became LLMs and building wrappers around them. It's like people forgot how to do ML.

      To those of us who actually trained models back in the day, its kind of cute to see people wowed by a classifier. Yes, this is 0 shot and doesn't need training (most people wanting this would've used structured output, this is cool because it's cheaper and faster). But anyone with basic ML knowledge could've built this in a few hours.

      The question is mostly why wasn't this productized. And it's interesting indeed that it took this long to become a finished product.

      [0] <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=9224">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=9224

      1. andai · · focus · HN ↗
        &gt; The question is mostly why wasn&#x27;t this productized.

        Probably because doing it wrong (using an llm in place of a classifier) is more profitable? (For the people selling inference.)

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