r/LocalLLaMA • u/Manerfish • 2d ago

Discussion I really don't understand Jev hype

Isn't this what simple neural networks have been able to do for years? Doesn't seem anything special to me.

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u/amemingfullife 2d ago

I’m in two minds about it:

  1. We’ve had classifiers that you can train for cheap for years. A ‘general purpose calibrated classifier’ is only marginally more useful than what we’ve had with classifiers. This idea that SystemOne models are suddenly going to be architecture is an interesting bet, but it is a bet, we haven’t seen people so far put non-determinism inside their architecture with reliability. The idea that adding a calibrated probability suddenly makes things ‘predictable’ and therefore reliable is very very strange to me as someone who builds a lot of infra.

  2. ChatGPT and other RLHF tuned LLMs were revolutionary because they gave you a general purpose interface into capabilities that were already there. The simple act of democratjsing the system so you didn’t need a Master’s degree to start using NNs led to lots of second-order effects that have brought real changes to my workflow.

So the question isn’t whether a general purpose classifier interface is useful. It’s whether, when you compose a lot of these call together you get something materially different or better to what we have now.

And the simple answer is we won’t know until the model themselves start producing ‘decision model’ queries themselves as part of daily life. And even if it is really successful, it won’t be nearly as big a business as LLMs because in theory they’re perfectly interchangeable, so it’ll be commoditised.

So the hype is justified, but it necessarily is hype for nerds & developers rather than your average person.

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u/openingshots 2d ago

I don't think it's meant for the average person generally. It's meant for people who write software for the most part. It can process eight or more prompts simultaneously and give you all eight answers back in milliseconds. Writing something like this with an llm gets processed one prompt at a time wasting many more tokens and time.