3 ms·
But I feel we're going back full circle. These small models are not generalist, thus not really LLMs at least in terms of objective. Recently there has been a r
by 3abiton 2y ago
But I feel we're going back full circle. These small models are not generalist, thus not really LLMs at least in terms of objective. Recently there has been a rise of "specialized" models that provide lots of values, but that's not why we were sold on LLMs.
- colechristensen 2y agoBut that's the thing, I don't need my ML model to be able to write me a sonnet about the history of beets, especially if I want to run it at home for specific tasks like as a programming assistant. I'm fine with and prefer specialist models in most cases.
- zeroCalories 2y agoI would love a model that knows SQL really well so I don't need to remember all the small details of the language. Beyond that, I don't see why the transformer architecture can't be applied to any problem that needs to predict sequences.
- dr_kiszonka 2y agoThe trick is to find such problems with enough training data and some market potential. I am terrible at it.
- Suppafly 2y agoSpecialized models work much better still for most stuff. Really we need an LLM to understand the input and then hand it off to a specialized model that actually provides good results.
- janalsncm 2y agoI think playing word games about what really counts as an LLM is a losing battle. It has become a marketing term, mostly. It’s better to have a functionalist point of view of “what can this thing do”.