alt Hacker NewsIt's technically sweet regardless, so don't take this as even a little bit of negative pushback, but I am curious what the utility of these small models is? Are they smart enough to be useful on practical tasks? What are people doing with them?
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If you work in a highly regulated space subject to e.g. HIPAA, and you work with ancient on-prem systems within a slow moving and risk intolerant organization -- for instance, virtually every state run healthcare system in the US -- then these are all you can hope for.
In these settings, data is insanely messy beyond your wildest nightmares and hidden away in free-text fields that small models like this are great at cleaning up, normalizing, parsing, categorizing, etc
This is an interesting question, so the idea is, based on experience, fine tuned small models can do narrow tasks very well (my experience running models fine-tuned on customer data as low as 1-2B is very promising) also the goal is to find a breakthrough were instead of the line of work (which I respect) that tries to squeeze much bigger models into smaller hardware like strata and maya, I'm working backward to discover/search for custom kernels and modifications till we exhaust the limit of what a smaller machine is capable of, so instead of people doing 64gb machines and old gpus to run a deepseek, I want to see what is the biggest usable qwen small model can run with reasonable speed on smaller devices, and by scaling as we discover more tricks, normal laptops can unlock more compute - for example a qwen 3.8 27B can do pretty serious work when coupled with a specialized harness - but we are yet to figure out what is the smallest machine that can run it with usable output and usable speed, and this can unlock interesting business.
Speech recognition, speech generation.
This alone is quite useful in small/limited devices/contexts.
Realtime log parsing and summarization is another application I've seen for little LLM's..
Basically, anywhere you'd use an LLM, but at much, much smaller scales of ontology.
Also curious on this. They are too dumb to use with tools and if you ask it how to bake a pancake you only get rubbish.
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Not op but my opinion is that It doesn't matter if it's not currently useful. I think it's important that the community focuses on this line of research because big companies will not. It's in their best interest to make LLMs resource hungry